NOTE TO USERS - University of Toronto T-Space · range of cost overnins for each of the Equipment, Labour and Material Costs on a construction project. Two completed p-ojects were

NOTE TO USERS

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Belief Network Analysis of Direct Cost Risk in Building Construction

Kevin Eyers

A thesis submitted in conforrnity with the requirements for the degree of Masters of Applied Science Graduate Department of Civil Engineering

University of Toronto

O Copyright by Kevin Eyers 200 1

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Abstract -- -- - --

Beiief Nehvork Analysis of Direct Cost Risk in Building Construction

Kevin Eyers

M.A.Sc. Department of Civil Engineering, University of Toronto, 200 1

Research was undertaken to develop a model to predict cost overruns on land-based,

North Amencan construction projects. A belief network model was chosen to meet this

goal. First, a catalogue of ail risks to construction cost was compiled. These risk

variables were ranked from most dependent variable to most independent variable to aid

in model development. Relationships between each of the risk variables on the list were

determined by surveying experts in the field. Thirdly, conditional probabilities for each

of the relationships in the model were calculated, again with the aid of expert surveys.

Finally, the model was calibrated using data fiom actual completed projects.

The user may set values of each of the vanables in the model, and read the likelihood of a

range of cost overnins for each of the Equipment, Labour and Material Costs on a

construction project. Two completed p-ojects were tested, and the differenccs between

actual and predicted cost overrun were found to be within 10%.

Belief Arenvork Anaiysis of Direct Cost Risk in Building Constnlcfion . . 11

Acknowledgements

For two years 1 have participated in the M.A.Sc. programme at the University of Toronto,

with the goal of contributing something o f value to the field of Construction Engineering

and Management. This research is the ~ e s u l t of that effort: and the contents of these

pages would not have been possible without the support, mentorship and guidance of

colleagues and fi-iends.

Professor Brenda McCabe has given me the opportunity to pursue this research. More

irnportantly, however, she has assisted me every step of the way. providing insight,

guidance and encouragement. 1 extend sincerest gratitude to her and thank her for her

dedication and support.

E would also like to thank Professor Tamer El-Diraby for his time and effort in reviewing

this research and sharing his ideas and comrnents.

The time and effort put foah by MGP Project Managers made the second and third

sections of this research, the sections requiring expert survey, possible. Paul Stein and

Sam Vaskov in particular were very helpful and supportive. In addition, I would like to

recognize the expert input of Ervin Arden, Peep Korgemagi, Cuthbert Radix, Cecil

Holtrop, Mark Doyle, and Cristina Segal.

Belief Nenrork -4nalysis o/Direa Cosr Risk in Birilding Consrrucrion ..- 111

Colleagues at the University of Toronto also provided guidance and assistance. I would

like to thank Daud Nasir: Roya Azad, Hrodny Njardardottir, Peter Pilateris and Joe

Ramani.

Away f?om the office, the unwavering support and love of family and friends helped to

motivate me to push on when times were tough. My parents? Brian and Cathy, along

with my brother and sister, Karen and Kyle- and my good friend Melanie Fairbrother

were aii there with words of encouragement when 1 needed them. I thank them

wholeheartedly.

Finally, 1 would like to acknowledge the financial support of the Ontario Government

Scholarship programme, the Department of Civil Engineering at the University of

Toronto, and MGP Project Managers.

Table of Contents

Abstract

Table of Contents

Table of Tables

Table of Figures

Table of Appendices

Chapter One: Scope and Objectives

1.1 Problem S tatement 1.2 Objectives of Research 1.3 Scope of Research 1 -4 Research Method

Chapter Two: Risk Basics, Mode1 Basics

2.1 Introduction 2.2 Construction Risks 2.3 Construction Cost Risks 2.4 Belief Networks

3-4.1 Introduction 2-42 Belief Network Terminology 2.4.3 Sample Evaluation 2-4.4 Belief Network Construction

2.5 Why Belief Networks?

Chapter Three: Risk Identification

3.1 Introduction 3.2 Risk List 3.3 Risk Categories

3 -3.1 Construction Risks 3 -3 -2 ContractuaVLegal Risks 3 -3.3 Management Risks 3 -3.4 Owner Risks 3.3.5 Design Risks 3 -3 -6 Project Characteristics Risks 3.3 -7 Location Risks

Belief A'envork Andysrs of Direct Cosr Risk in Building Cons~nrcrion v

3 -3 -8 Economic Risks 3 -3 -9 Political Risks 3 -3.10 Environment RÏsks

3 -4 Risk List Ranking 3.5 Risk State Definition 3 -6 Divorcing Variables 3 -7 Predictor Variables

Chapter Four: Relationship Identification

4.1 Introduction 4.2 Expert Survey 4.3 Survey Results Andysis 4-4 Literature Search 4.5 Divorcing 4-6 Data Reduction

4.6.1 Relationship Elimination:

4.6.2 Relations hip Elimination:

4 - 6 3 Relationship Elimination:



Cliapter Five: Probability Determination

5.1 Introduction 5.2 Data Reduction

5.2.1 Asymmetric Assessrnent

Tenant Reqztirement Change - Design CZaims Qrral9ed Local Labour - Labozlr Delays Local Suirab le 1Mcrrerials - Projecr Material Shortage Tenunt Reqtrirernent Change - Design Changes Design Tearn Coordination - 45 Design Changes

48

5.2.2 Parent State Combination Ranking 5 -3.3 Probability Curve Development

5.2.3.1 Probability Curve Parent State Ranking 5.2.3 -2 Probability Cumes 5.2.3.3 Divorcing Cuves

5.3 Probability Expert Survey 5.3.1 Expert Survey Development 5.3.2 Survey Data Analysis

5.4 MSBNTM Model 5.4.1 Model Construction 5.4.2 MSBNTM Text File 5.4.3 Using the Model

Belief iVenr.ork Analysis of Direct Cosr Risk in Building Consfnrcrion vi

Chapter Six: Model VerificatiodValidation

6 - 1 Introduction 6.2 Sensitivity Andysis 6-3 Model Validation

6.3.1 Project One: ABC Manufacturing Facility 6.3 -2 Project Two: 123 Company Building Envelope

Restoration 6.3 -3 Validation Discussion

Chapter Seven: Conclusions

7.1 Conclusions 7.2 Contributions 7.3 Recommendations

References

Appendices

Bei~ef Nenvork Analysis of Direct Cosr Risk in Building Consrnicrion vii

Table of Tables

Table 1.1

Table 2.1

Table 3.1

Table 3.2

Table 3.3

Table 3 -4

Table 3.5

Table 3.6

Table 3.7

Table 3.8

Table 3 -9

Table 3.10

Table 3.1 1

Table 3.12

Table 4.1

Table 4.2

Table 4.3

Table 4.4

Table 4.5

Table 5.1

Table 5.2

Research Methodology

Mathematical Notation

Appendix A Columns

Construction Risks

ContractualLegal Risks

Management Risks

Owner Risks

Design Risks

Project Characteristics Risks

Location Risks

Economic Risks

Political Risks

Environrnent Risks

Ranked List of Construction Cost Risks

Relationship S w e y Rejection Tests

Relationship Survey Acceptance Tests

Borderline Relationships eliminated as a result of expert analysis

Variable Relationships identified in Lirerature Study

Divorcing the Construcrion Claims Variab le

Regression of Parent State-interpolated variables

Difference between interpolated values and surveyed values

Beltej:Venr.ork -4nalysis o j Direct Cos! Risk in Bzttlding Constnrclion ... V l l l

Table 5.3 Strength of Parent Variables on Equiprnent Cost predictor variable

Table 5.4 Exarnple Ranking Calculation

Table 5.5 Appendix G SarnpIe

Table 5.6 Appendix H Sarnple

Table 5.7 Division of questions on the probability survey

Table 6.1 Predicted likelihood of various cost overruns for each cost Category, ABC Manufacturing Facility

Table 6.2 Predicted likelihood of various cost o v e m s for each cost category, 123 Company Building

Brlief Nenvork Anaiysis of Direcr COSI Risk in Buildrng Consrnrcrron ix

Table of Figures

Figure 2.1

Figure 2 2

Figure 4- 1

Figure 4-2

Figure 4-3

Figure 4.4

Fi,oure 5.1

Figure 5.2

Figure 5.3

Figure 5.4

Figure 5.5

Figure 5.6

Figure 5.7

Figure 5.8

Fibgure 5.9

Figure 5.10

Sarnple Belief Network

"A" is a child of "B"

Sarnple Relationship Identification Survey

Non-divorced Construction Claims Variable

Divorced Constrzrction Claims Variable

Completed Belief Network Mode1 Structure

Asymrnetric Assessment structure for Project Mcrterial Shortcrge

Ranking from most severe conditions to least severe conditions, Overrime child variable

Probability Curves for Predictor variables

Sample Probability Survey

Example of Situation where average value was not selected

Text file node definition - Srrituble Eqzlipmenr Availubility

Suitable Equipmenr Availnbilify Conditional Probabilities

Asyrnrnetric Assessrnent Structure - Suitable Equiprnent Availabilii'y Text File

Asymrnetric Assessment Structure - Szrituble Equipment Availubilify Graphical File

Sarnple MSBN Evaluation

Belie/:Venvork Analysts of Direc! Cos! Risk in Building Consrnicrion X

Table of Appendices

Appendix A Risk Variable Information 92

Appendix B Risk Relationship S w e y 100

Appendix C Risk S w e y Analysis 106

Appendis D Divorcing 116

Appendix E Asyrnmetrk Assessrnent Structures 119

Appendix F Cornparison: Probability Survey Interpolated Values to S w e y Values

Appendix G

Appendix H

Appendix 1

Appendix J

Appendix K

Appendix L

Appendix M

Probability Curves

Predictor Variable Ranking

Probability Survey Results, Prior ProbabiIities

Divorcing Variable Ranking

Data Reduction Description

MSBN Test File

Mode1 Validation Results

Belief iVenvork Anabsis of Direcr Cosr Risk in Building Consrnicrion xi

For Laura

Chapter One: Scope and Objectives

1 . PROBLEM STATEMENT

Construction projects are subject to enormous uncertainty. In general, the greater the size

and duration of the project, the greater the uncertainty that exists. Long-term projects are

particularly prone to cost and schedule overruns; there is great uncertainty in trying to

predict what may occur several years into the future. As such, it is important that al1

project participants (owners, project and construction managers, contractors,

subcontractors, bonding and insurance agencies, etc.) have a good grasp of events that

rnay befall their project, and the likelihood that these events will occur.

Recent research focused on the identification of schedule risks, determination of the

likelihood of these risks, and their effects on overall project schedule (Nasir, 2000). In

addition, work is being done on the identification of risks to budget, and their effects on

final project cost (Elhag and Boussabaine, 2000). However, no work to date has been

found that predicts cost overnins in a probabiIistic marner.

What is the likelihood that the project cost will exceed the original project budget,

and by how much, given current conditions?

Answers to questions ILke L ~ S provide project participants with the opporhmity to

undertake corrective mesures to bring project cost back to the estimated budget cost.

The ability to address budget concerns during the course of a project is greater when the

project is long-term; therefore, while more risk exists, more opporhmity exists to fix

Belief Nenvork Anaipis o j Direct Cost Risk in 611ilding Construction 1

problems before they seriously affect the final outcome of a long-term project. This

report deals with the assessment of degree of, and associated likelihood of, cost overrun

on long-term projects.

Studies have been conducted on determinhg the risks associated with cost overruns

(Elhag and Boussabaine 1999, Mulholland and Christian 1999). However, none predicts

cost risks in a manner that attaches probabilities to each degree of ove rm. Additionally,

a need was identified to gain a better understanding of the interaction between the

variables affecting project costs.

The primary objective of this research is:

to develop a model that will predict the most Iikely cost overrun for each of the

major cost centres in a long-term building project budget

While the development of such a model is the primary focus of this work, several

preliminary steps were of academic and practicd value, and served as milestones

throughout the thesis. These preliminary goals include

1. identi@ing factors affecting the cost of construction projects,

2. determination of the manner in which these factors affect cost,

3. development of a more efficient expert surveying method,

4. determination of the degree to which these variables affect cost.

Each of these preliminary steps led to the development of a Bayesian belief network

model that accomplished the primary objective of this research.

Belief Nenvork iinafysis of Dlrecr Cos! Risk in Building Conslruclion 2

1.3 SCOPE OF RESEARCH

This research deals with construction projects that have the following characteristics:

Long-Term

"Long-term" refers to the fact that the time value of money plays a role. If

the duration of the project is long enough that inflation and construction

market escaiation need to be considered, then the project is considered to

be long-term. There is much more uncertainty in the construction of large

projects simply because of the time and resources that need be committed

to their construction. The author believes that ~here is more to be gained

by studying long-term construction than short tem.

Land-Based

There are many additional factors that corne into play in the construction

of offshore projects. Facilities like the Hibernia oil fields encounter risks

that do not affect land-based construction projects. This mode1 does not

consider such factors.

Preliminary Design Only Necessarily Complete (Le. assume project is fast-tracked)

The mode1 assumes that only the preliminary design is necessarily

complete. Most long-terrn construction projects these days are constructed

on a fast-track basis. That is, they are designed as construction proceeds -

design drawings become available as construction requires them. As a

result, only some detailed drawings are complete at the commencement of

Belief lVenrork Analqsis o j Drrecr Cosr Rtsk in Building Consrnicrion 3

construction. On the other hand, gross design drawings are necessary to

begin building. This model is useful at any point afier prelirninary design

is cornpiete.

Mistake-Free Budget Estirnate

This work seeks to identifi the probability of cost overrun. As such, it is

necessary to have a budget to which the final actual cost can be compared.

It is also necessary to assume that this budget estimate is correct.

Additional risk in the forrn of the possibility of an inaccurate estimate

rnust be considered if this assumption is not met. This model makes no

such allowance.

Based in the United States or Canada

Construction takes place under different circumstances al1 over the world.

On the other hand, Canada and the United States have similar construction

environrnents in which to work. To eliminate differences that may occur

due to construction projects overseas or in third world countries and the

like, the scope of this model has been limited to the relatively stable and

sirnila. environments of Canada and the U.S..

Contractors are Pre-Qualified and Bonded

Large construction projects require owners and project managers to be

concerned about the ability and experience of the construction

Belief Xenvork Anulysis of D~recr Cos! Risk in Building Consrmcrion 4

participants. To that end, project owners go to great lengths to ensure that

al1 participants are competent and able to do the work efficiently. The

means that they use to gain this assurance are pre-quaIification and

bonding. Pre-qualification ensures that d l project bidders have shown the

ability to do similar work in the past. whiile bonding protects the owner in

the event that the work does not get completed due to insolvency.

Only Building Construction considered

Only elements of building construction are considered. Infrastructure and

residential construction projects, for exarnple, are not included in the

scope of this research.

Four main steps were taken in the development of this model. The four steps, described

in more detail throughout the report, are shown i n Table 1.1. Since sirnilar research using

Belief Networks was conducted at the University of Toronto for schedule risks in

construction (Nasir 2000), similar methodology was therefore used.

Belie f Nenvork A nalysis of Direct COSI Risk in Buddrng Consrntction 5

~ 1 or in combination, have an effect on 1 with some informal expert II

Table 1.1: Research Methodology

Quantification 1 every parent state combination for 1 II

Primary Research Techniques Literature search prirnarily, along

S tep Risk Identification

1

I

Relationship Identification

Relationship

Description Identi@ ail factors that, either alone

1 1 actual direct cost overruns

direct costs in construction Determine most significant cause- effect relationsliips for every variable identified in the Risk identification step Calculate conditiona1 probability o f

Mode1 Verificatiod Validation

The four steps identified in Table 1.1 are typical steps used in the development of Belief

interview PrimariIy expert survey (approximately 90%) along with a minor literature searzh (1 0%)

Exclusively expert survey

Networks (McCabe et al, 1998). A study of al1 available literature was conducted to

every variable in the mode1 Ensure that the mode! is predicting reasonabIe values

identify al1 risk variables to cost on construction projects that meet the limitations of the

Using completed projects, compare predicted direct cost overruns with

research scope as described previously. This literature search identified any causal

relationships between chosen risk variables. As a suppIement to the literature search,

informal expert interviews were conducted to gain additional insight into direct cost risks

in construction. The Iist of risks was then ranked to aid in rnodel development, and States

were identified for each of the variables included in the model.

Secondly an expert survey, in matrix format, was created to identiQ cause-effect

relationships between each of the risks identified in step one. For each "effect variable",

the strength of relationship with every appropriate "cause variable" was determined, and

the strongest relationships were retained for use in the rnodel. This ensured that

important model relationships were included, while weaker relationships that increase

model complexity more than they increase model completeness were excluded. To

increase the ease with which the experts could complete what was admittedly a

Belie/;Venvork rlnalysis O/ Direct Cost Risk in Buiiding Consfruction 6

complicated s w e y . the author was available at al1 times via e-mail or telephone to

answer questions.

Experts were chosen fiom a pool of project management experts at MGP Project

Managers, project managers at the Lester B. Pearson International Airport new terminal

construction in Toronto. The experts were chosen to reflect a wide range of expertise and

expenence.

At this stage. every variable had been assigned between zero and six parent variables.

For every variable, each combination of causal variable and effect variable states was

assigned a probability between 1 - 100: reflective of the likelihood that the causal variable

state combination would produce the effect variable state. An expert survey was used

exclusively to this end. A structured interview process was the method of survey chosen

for this stage of research. This made it easier for experts to complete the survey, which

in many cases needed quite a bit of clarification.

Finally, information regarding actual cornpleted projects was used in the model to arrive

at a predicted direct cost overrun. This cost overrun was compared to the actual direct

cost oven-un, and a statement about the effectiveness of the completed model made.

Beirejh'envork Analysts o/Direcr Cos1 Risk m Brddrng Cons!nrcrron 7

Chapter Two: Risk Basics, Mode1 Basics

2.1 INTRODUCTION

Risk is a concept with many definitions depending on the perspective of the individual

defining it. At its most basic. risk can be categorized as "1. The possibility of suffering

harm or loss; danger ... 2. A factor, elemenf or course involving uncertain danger; a

hazard." (Webster, 1990). This definition is, at best, rudimentary. The Construction

Industry Institute (1989) goes further, stating that risk is the probability that an

davourable outcorne will occur. Conversely, the probability that a favourable outcome

will occur is defuied as opportunity. Risk and opportunity go hand in hand. High-risk

situations are usually accompanied by the potential for great reward. On the other hand,

if the potential for reward is great, one should beware of the fact that the situation is

likely quite risky as well. This risk-reward partnership is especially evident in

construction.

2.2 CONSTRUCTION RISKS

Long-term projects costing in the billions of dollars are subject to tremendous amounts of

uncertainty, not the least of which has to do with the fact that these types of projects

occur over several years (witness the 10-year, $4.4 Billion prograrn of construction at

Lester B. Pearson International Airport in Toronto). It is impossible to completely and

accurately predict what may or may not occur over a 10-year planning horizon; $4.4

billion is a large sum of money to risk, given that degree of uncertainty. Constmctors are

especially focused on two main categories: scheduie risks and cost risks. Research on

Belief Nenrork Anaiysis of Direct Cosr Risk in B u i l h g Consrnrcrion 8

schedule risks using Belief Nehvorks has already been undertaken. This work focuses on

risks to cost,

2.3 CONSTRUCTION COST RISKS

Ultimately, construction is undertaken by contractors in order to earn profits. Project

owners have different goals, such as the construction of facilities that fit their needs. An

important goal of construction fiom the owner's point of view is to have the project

completed on time, and on or under budget. Cost is, therefore, of the uûnost importance

to al1 parties involved with a construction project.

Project managers w-ith years of accumulated experience develop instincts about what may

go wrong on their projects. It is important to capture these intuitions as well as possible

in a mode1 like this. As such, every risk factor needs to be catalogued and analyzed.

These risk variables include factors that can be affected by management (labour

productivity and overtime, for exarnple) as well as factors that are outside human control

(e-g. geology, natural disasters).

2.4 BELIEF NETWORKS

2.4.1 INTRODUCTION

First developed at Stanford in the 1970s, the Bayesian belief network is a forrn of

artificial intelligence that has only recently gained some acceptance in construction

applications. The Belief Network is a flexible modeling tool that allows the modeler to

Befie/Xenvork Analysis of Direct Cosr Risk in Building Consrnrcrion 9

not only predict the outcome of a situation, but also predict the probability of a range of

different outcomes (McCabe et al. 1998).

A belief network is a collection of nodes, representing mode1 variables, and directed arcs

(arrows) denoting dependent relationships between variables (Pearl 1 996)- Belief

Networks are "directed acyclic graphs'' (DAGs), meaning that the arrows cannot be

directed away fiom a node to other nodes, and then back to the original

is used to illustrate terminology associated with belief networks.

4cceptable Productivit b

node. Figure 2.1

Figure 2.1: Sampie belief network, (McCabe et al., 1998)

The nodes such as Too Few Loaders denote the factors being studied, while the arcs

denote the relationships between factors. Beside each node are the conditional

probabilities that apply to that particular node and its parents (Le. the nodes that affect it).

In this belief network, the number of loaders and the number of trucks have an effect on

the effrciency and productivity of a truck loading operation. Too few ioaders or too many

trucks, and a queue may forrn (Acceptable Queuina). The length of the queues affect the

productivity of the system. In addition, the number of trucks used aiso affects the

integrity of the road surface (Sozmd Roud Surface).

Belief ~Venvork ..lnuiysis of Direct Cosr Risk in Building Constntcrion 10

For clarity throughout the report, variable names will be s h o w in italic. Section 2.4.2 is

a co1Iection of terms needed to understand discussions of belief networks. Following

that, Section 2.43 provides an exarnple of the calculations perfonned in belief network

evaluation.

Throughout this thesis, the notation fiom propositional caiculus in Table 2.1 will be used.

Notation P(TFL)

Table 2.1: Mathematical Notation Definition Denotes the probability that there are Too Few Loaders Denotes the probability of variable Acceptable Productivity? given that there is acceptable queuing Denotes '&andn - P(AQ&) denotes the probability that acceptable queuing and acceptable productivity occur Denotes the negative state - P(-AQ) denotes the probability of unacceptable queuing

2.4.2 BEL~EF NETWORK TERMINOLOGY

The following is a list of terms used in discussing belief networks.

Baves' Theorem: Bayes' Theorem deals with conditional probabilities. In belief

networks, Bayes' Theorem is used to revise the belief about the state of one variable

given the States of al1 other variables in the network. Bayes' Theorem stipulates that:

(1) (singIe variable influence)

(2) (multiple variable influence)

Belief Xehvork Analps of Direct COS[ Risk rn Building Consrnrcrion 11

Child: Node "A" is a child of Node "B" if an arc orïginates at Node " B and terminates at

Node "AY'- In Figure 2.1, Acceptable @elring is a child of both Tou Few Loaders and

Figure 2.2: "A" is a child of "B"

D-separation: In the example network, Too Many Trucks affects Acceptable Quezring,

which in turn affects AcceptrrbZe Productivi&. Too Many Trzicks clearly has an affect on

Acceptubk Productivi~ through Acceptable Queuing. On the other hand, if the state of

Acceptable Qzreuing is known, then the state of Acceptable Productivity is not at d l

dependent on Too Muny Trucks. Acceptable Productivity and Too Many Trucks are said

to be d-separated by the instantiation of the intermediate node AQ. This is a very usefui

property of beiief networks, and allows vast simplification of calculations. The example

calcdations perfomed in the next section will demonstrate this effect.

Instantiation: A node is instantiated when its value is known. If, for example, it becomes

known that Sound Roud Szrfice is fdse in Figure 2.1, the variable SRS is said to be

instantiated. If SRS-rio, it means that the road surface is not sound, and that P(-SRS) =

1, and P(SRS) = 0.

Orphan: A node is an orphan if it has no parents. In the Figure 2.1, Tou Few Loaders and

Too Muny Trucks are both orphans.

BelieJiVenvork rlnalysis of Direcr Cosr Risk in Bitilding Comrnrcrion 12

Parent: Node A is a parent of Node B if an arc originates at Node A and terminates at

Node B. In the Figure 2.1' Too Many Tmch is a parent of both Acceptable eueuhg and

Sound Road Surface.

Variable State: A variable may take on different values. In a belief network, these values

are cdled "States". Each of the variables in the sarnple network has two States (Le. they

are binary). In general, variables need not necessarily be binary.

2.4.3 SAMPLE EVALUATION

The following is an exarnple evaluation of the sarnple network. The evaluation is taken

from (McCabe et al., 1998) and is based on Figure 2.1.

Problem: Determine the likelihood that there are too many trucks in the system, given

that the road has deteriorated and the productivity of the system is acceptable. In effect,

find:

~(TMTIAPA-SRS) (Problem Equation)

Step 1 : Use Bayes' Theorem to condition the previous statement on a parent

P(TMT 1 AP A -SRS) = P(AP A 4 R S 1 TMT) * P(TMT)

P(AP A --SRS) (Eq- 1)

P(TMT) can be read directly from Figure 2.1. The remaining phrases need additional

manipulation before they can be taken from the belief network.

Belief Nenvork Analysis of Direct Cost Risk in Building Construcrion 13

Step 2: Use the concept of d-separation to simplify P(APA-SRSITMT). Since the state of

TMT is given in this statement? AP and SRS are d-separated, and therefore independent.

so,

P(AP"-SRS [TMT) = P(AP/TMT)* P(-SRS (TMT) (Eq. 2)

Now, P(TMT) and P(-SRSITMT) can be extracted from Figure 2.1. Remaining

unknown values include P(AP/TMT) and P(APA-SRS).

Stev 3: Condition the probability of AP on al1 parents of AP, given the evidence that

TMT = true.

P(AP(TMT)=P(APITMTAAQ)*P(AQITMT)+P(API-AQ)*P(-AQlTMT) (Eq. 3)

Note: AP and TMT are d-separated by AQ, so the probability of AP depends only on AQ.

Therefore,

P(APITMTAAQ) = P(AP1AQ) (Eq. 4)

Step 4: Determine P(AQ1TMT). Note that P(-AQITMT) = 1 - P(AQ1TMT).

P(AQ1TMT) = P(AQITMTATFL)*P(TFL)+P(AQfTMTA-TFL)*P(TFL) (Eq. 5)

Al1 four right-hand-side values are known. Only the denominator remains to be

evaluated.

P(TMT), P(-SRSITMT), P(APIAQ), P(AQITMTATFL), P(TFL), P(AQ/TMTA-TFL),

P(-TFL), P(-AQ[TMT)=l-P(AQ(TMT) can al1 be taken from the beiief network in

Figure 2.1. P(APh-SRS) remains.

BeliejArenvork Analysis of Direct Cost Risk in Building Comtn~crion 14

Step 5: Evaiuate the denorninator:

P(AP"-SRS) = f (-SRSIAP)*P(AP) (Eq. 6 )

Note: P(-SRSIAP) = 1-P(SRS/AP) (Eq. 7)

Therefore,

1 -P(SRSIAP) = 1 -[P(SRSIAPATMT)*P(TMTIAE') + P(SRSIAPA-TMT)*P(-TMTIAP)]

Where ,

Since SRS and AP are d-separated by TMT,

P(SRSIAPATMT)=P(SRSITMT) (Eq.9)

EveIything except P(AP) has been evaluated.

Step 6: Evaluate P(AP) by conditioning on a11 parents.

P(AP) = P(APIAQ)*P(AQ)+P(API-AQ)*P(-AQ) (Eq. 10)

where,

P(AQ)=P(AQ[TFLATMT)*P(TFL)*P(TMT)

tP(AQITFLA-TMT)*P(TFL)*P(-TMT)

+P(AQI-TFLATMT)*P(-TFL)*P(TMT)

tP(AQ1-TFLA-TMT)*P(-TFL) "P(-TMT) (Eq. 1 1 )

Step 7: Work backwards through the calculations to arrive at the desired outcome

By Eq. 11, P(AQ) = 0.05*0.5*0.5+0.35*0.5*0.5+0.35*0.5*00.9*05*0 = 0.413

By Eq. 10 P(AP)=0.85*0.413+0.15*0.587=0.439

By Eq. 8 P(TMTIAP)=0.29*0.5/0.43 9 = 0.330

Belief Nenvork Anaiys;s 01 Direct Cosr Risk in Building Consrnicrion 15

By Eq. 7 P(-SRSIAP)=l -(O. lS*O.330+0.9*0.670) = 0.348

By Eq. 6 P(APA-SRS)=O-348*0.439 = 0- 1%

By Eq. 5 P(AQ[TMT)=0.05*0.5+0.3 5*O-j=O.2

By Eq. 3 P(AP~TMT)=0.85*0.2+0.15*0.8= 0.290

By Eq. 2 P(AP-SRSITMT)=O.29*0-85 = 0.247

Therefore,

(Problem Equation) P(TMTIAPA-SRS)=O.~~~*OS/O. 153 = 0.807

Step 8: Conclude:

It may be concluded with 8 1% confidence that there are too many trucks in the system, or

P(TMTIAPA-SRS) = 8 1%.

2.4.4 BELIEF NETWORK CONSTRUCTION

Four main steps need be taken in the development of a belief network (Poole et al. 1998).

They are:

1. Define relevant variables and identifi variable States

2. Define variable relationships

3. Determine conditional probabilities of relationships

4. VeriQ and validate the network

Each of these four steps is taken in the development of the mode1 for this thesis, and will

be discussed in one of four chapters devoted to the cost mode1 construction.

Belief h'envork ilnalysis of Direcr COSI Risk in Building Constntcrion 16

2.5 WHY BELIEF NETWORKS?

The main alternatives to the belief network for the type of mode1 to be used in thLs

research are Neural Networks, Linear / Dynamic Programming, Regression Analysis, and

Simulation / Risk Analysis. Some limitations of these types of models include (Elhag and

Boussabaine, 1999):

+ Unknown combined effects and interrelationships of cost risk variables

0 Imprecision and uncertainty of data and variables affecting costs of

construction projects

Belief Networks not only allow examination of these combined effects, they also seek to

quanti@ the uncertainty of data and variables, and allow probabilistic analysis. In the

sarnple evaluation, it was deterrnined, with 81% certainty, that there were too many

trucks in the system. Neural networks do not intrinsically allow for this quantification of

degree of belief. Because this research attempts to quanti@ uncertainty, the probabilistic

basis was important, In addition, neural networks require a tremendous amount of

historical data to train the network (Portas and AbourRizk 1997). These data were

simply not available to the author of this work as each project data would have to be

collected individually where it was even possible to collect it.

Another benefit of belief networks is their flexibility. Nodes may be added to or

subtracted from the network if it is deemed necessary by any user. AIso, evidence for

every variable need not be gathered. Either of these changes would require complete

reconstruction and training of a neural network.

Belief A'enrwk Analysis of Direct Cosr Risk in Building Constn~rion 17

At the time of this research Elhag and Boussabaine were using neural networks to deal

with this problem. Their model most closely resembles the research done in this rnodel.

Cost risk variables were collected and grouped according to their main effect on cost.

The researchers then ranked the risk variables according to the magnitude of their effect

on final project cost. The research m e r proposes to use neural networks and fuzzy

logic to predict final project cost and schedule overmns. The neural network portion of

this research is not yet complete. As a result of the fact that neural networks are being

used for similar research. a different approach was sought to attack the problem.

Ln the final analysis it was detennined that, for the reasons detailed above, the belief

network was the best type of model to be used in this research. The subsequent chapters

of this report detail the steps taken in the construction of a belief network to predict cost

ovenruns on construction projects.

Belief .Vencork Anaipis of Direct Cosr Risk in Building Consrnrcrron 18

Chanter Three - Risk Identification

3.1 INTRODUCTION

A search of available Iiterature was conducted to identiq factors affecting cost on

construction projects. Factors that affect cost in a direct manner, as well as those that

acted indirectly (Le. through other factors) were studied. In the end, a Iist of 75 risk

variables affecting construction costs was compiled. The risk variables chosen were

carefdly defined so that relationships could be established at a Iater stage. This list \vas

then r d e d so that any given risk on the list may only be affected by risk variables lower

on the list. Finally, risk States were detemiined for each of the variables. Each of these

stages in the risk identification process will now be discussed in M e r detail.

3.2 RISKLIST

Several sources were studied for factors affecting construction cost. After reviewing

available literature, it was determined that no research had yet produced a compilation of

al1 risks to construction cost. As a result, information fiom several sources, including

textbooks, journal articles, and persona1 expert interviews were compiled into a master

list. A paper was later discovered that included a similar compilation of factors affecting

construction cost (Elhag and Boussabaine 1999). The two lists of construction cost risk

variables were compared, and found to contain a similar collection of variables. Where

factors were missing from this research list, they were either added or included in the

definition of variables already in the collection.

Belief Xenrork Anaiysis of Direct COSI Risk in Brrrld~ng Consrnrcrion 19

There are ten different categones of nsk identified in this research. Each of the 75 risks

to cost discovered in the literature search is classified in one of the ten categories.

Appendix A contains a list of al1 risk variables used in the development of this belief

network model, ranked fiom most dependent to most independent, with al1 variable states

definitions, and ~Iassifications listed. The columns in the appendix are listed and

explained in Table 3.12.

3.3.1 CONSTRUCTION Rrs~s

Construction risks, in the context of this project, are defined as risk variables that occur

as a direct result of, or directly affect the building construction. If one studies the risk

variables in this group, it is apparent that these are risks rnost affected by. or under the

control of the main contractors on site. The construction risk variables are shown in

Table 3.1: Appendiv A columns

Table 3.2.

Column Heading Ris k Name/Source Risk Definition Risk States Risk Parents

The first three variables- equipment cost, labour cost and materid cost are the three

variable used to predict the actual project cost, which c m then be compared to the

budgeted cost. These three "predictor variables" will be discussed in more detail Iater in

this chapter.

Definition The name of the variabIe and the prirnary Iiterature source in which it was found A short explanation of the variable A list of al1 of the variable states that the variable may take on A Iist of al1 the variables that have a direct effect on the respective rïsk variable

Belief Xenrork Anaiysis of Direct Cost Ris& in Budding Constntct~on 20

Table 3.2: Construction Risks - - -

1 Risk 1 Source W Equipment Cost Labour Cost Material Cost

CI1 1989 CH 1989 CI1 1989

Il Overtime Construction Delavs

L

CII 1989, Thomas 1992 CI1 1989

Failure Delays Labour Productivity Work Quantity Deviations Matenal S hortage Material Waste Defective Work Equipment Productivity Material/Eaui~ment Loss

1 Flanagan and Norman 1993 Wideman 1992, Thomas and Napolitan 1993 CI1 1989 Nasir 2000 CI1 1989 .

- -- -

CI1 1989 Wideman 1992 CI1 1990

1 .l

Often, construction costs are impacted significantly by the project schedule. Factors that

Labour Injuries/Accidents Archaeo logical Survey Construction/Operations Interference Trafic Congestion Number of Workers on Site Construction TechnoIogy

cause the project to lag behind schedule may also indirectly put strain on the project

CI1 1989, Hinze et al 1998 Nasir 2000 E.upert Interview CI1 1989 CI1 1989 CI1 1989

budget. For example, overtime costs more than regular time, and as a result, adversely

affects project cost. Other factors related to the project schedule are construction delays,

participant failure delays, labour productivity, equipment productivity,

construction/operations interference, and traffic congestion on site. Each of these factors

alone or in combination can cause a project to fa11 behind schedule and increase cost as a

result.

Work quantity deviations, material waste, and defective work al1 affect the material

quantities that are used on the project. This has a direct impact on project material cost,

as does the use of foreign purchased goods and services.

Belief Nenvork Anaiysis of Direcf Cost Risk in Brriiding Constnrcrion 21

Finally, material/equipment loss/darnage, labour injuriedaccidents, the number of

workers on site, and technology requirements directly or indirectly affect the cost of a

building project.

Projects of a large magnitude such as those being studied in this research require very

significant contractual and legal agreements. It is quite important to t&e account of these

arrangements to gain a full understanding of the environment in which a project exists.

Table 3.3 outlines these risks.

Contract clauses create the iegal environment under which the project participants

operate. In conjunction with the contractor payment type, they also determine the party

to which the cost risk on the project is transferred, This risk can either be accepted by the

contractor, the owner, or shared by both parties.

Table 3.3: Contractual/Legal Risks

Construction claims c m cause significant project delays and cost increases. Claims c m

also serve to create animosity between interested parties, thus affecting future work on

the project,

Ris k Construction CIaims Contract Clauses Contractor Payment Type

Especially on large projects, project management iç a crucial elernent of cost control.

Source CU 1989, Diekman and Nelson 1985 CI1 1989 CI1 1989

Projects that are well organized and managed stand a better chance of finishing on time

Beitef Xenvork rlnaiysis of Direct Cosr Risk in Btrilding Consmcr~on 22

and on budget @ozzi et al. 1996). There are a number 04 factors that make up project

management, but the variable that al1 others are related IO is the composition of the

project management (PM) tearn itself. Table 3.4 outlines al1 of the factors included in

this mode1 that relate to the management of the project.

Table 3.4: Management R i s k Ris k Cost Accountino

Cooperative Environment 1 Expert Interview, Larson 1997, McMarnamy 1997 Il

- - -

Source Ex~er t Interview I

Y

Trade Coordination Long Work Stoppages Materials DeIiverv

Wideman 1992 CI1 1989, Zack 1997 CI1 1989

PM knowledge of area 1 CI1 1989 11 PM PM work familiaritv

Qualified key PM personnel 1 CI1 1989

The availability of PM personnel, their knowledpe of the area. farniliarity with the type of

Expert Interview, Dozzi et al, 1996 CI1 1989

work being done, and their comrnitment to the project goals are factors that directly affect

1

how well the project is organized, and consequently the smccess or failure of the project

in relation to the budget and schedule.

One event that occurs on many projects is a prolonged work stoppage due to a labour

dispute. Strikes c m affect project schedules and deadlimes, again indirectly affecting

project cost. They can also cause construction clairns for either extra time or money by

other project participants, directly increasing costs. One w a y to mitigate such claims is

by the use of Partnering. Partnering is a management technique pioneered by the US .

Army Corps of Engineers in 1983 in response to $1 B in outstanding clairns and appeals.

Partnering has been shown to improve relationships on building projects and these

improved relationships can lead to improved Trade Coordination, and more prompt

Beliej Arenvork Analysis of Direcr Cost Risk in Building Constnicrton 23

Materials Delivery. These are two other management factors found to affect cost on

long-term construction projects.

Finally, cost control is highly dependent on accurate and timely cost reporting and

accounting- Project managers that keep carefùl track of costs on a consistent basis stand

a better chance of spotting problems and addressing them before they get out of control

and seriously affect the final project cost.

3.3.4 OWNER RISKS

The project owner uitimately makes d l decisions with regards to project construction -

the owner is in charge. As a result, the project owner has a significant impact on whether

the project finishes on budget. The type of owner determines the h d i n g source

(government, private, or some combination). The fùnding source, and financial stability

of the owner and this significantly affects the project philosophy regarding factors such

as budget revisions. In short, the ow-ner establishes the fiscal environment under which

the project is built. Table 3.5 shows al1 risk variables related to project ownership.

Table 3.5: Owner Risks r

One of the major cornponents of any construction project is the design of the building to

Ris k Budget Revisions

I

be constmcted. Construction cannot be completed prior to the submittd of design

Source Expert Interview

documents. It should be noted that the scope of this project is Limited to fast-track

Belief Nenvork Anaq'sis of Direct Cosr Risk in Building Consrnrcrion 24

Funding Source Owner Financial Stabiliw

Wideman 1992 CI1 1989 1

projects, that is, projects that are built while many of the design documents are still being

completed. Designs are produced as the construction requires them. Table 3.6 lists the

risk variables in this category-

Table 3.6: Desim Risks Ris k

Design Submittal Design Quatity

11 Tenant ~ e a u i r e r n e n t ~ h k s e -

Complexity/ConstructabiIity of Design Design Team Coordination

- Source Design News 1997 Flanaean and Norman 1993. Hester and Ku~renas 1987 Arditi and Gunaydin 1998 CE1 1990 CI1 1989 E x ~ e r t interview

Expert Interview 1

Because there is Iittle tirne in between design submittal and the use of design documents

in construction, timely production of a quality design is crucial in keeping the project on

schedule, and consequentiy, on budget. Changes to designs resdt in late design submittal

and problems such as defective work and reduced productivity, as do scope creep,

complex designs and changes in tenant requirements.

Three effective methods for reducing the cost of construction at the design stage are good

communication, coordination of design tearns and Value Engineering. Value

Engineering is an efFective design practice because redundancies in design are

eliminated, costs are saved, and problems anticipated. The project may, as a result, be

built more efficiently.

3.3.6 PROJECT CHARACTERISTICS ~ S K S

The type of project and its characteristics largely deterrnine the ease with which a

building may be constructed. Table 3.7 lists the risk variables in this category.

Belref Nenvork Analysis of Direct Cosr Risk in Building Consrnrction 25

Access and egress to the site? physical project size and other competing activity on site

Table 3.7: Project Characteristics Risks

are three factors that are critical determinants of the amount of congestion on site. They

Ris k Site Security Site Access Physical Project Size Cornpeting Activity on Site

also affect the ability of project supervisors to secure the site, thus protecting the project

Source CI1 1989 Expert Interview Expert Interview CI1 1989

from materials or equipment thefi. These characteristics are 1argeIy determined by the

location of the project and the previous use of the project site. Projects that are built on

land previously used for other purposes, or large-scale renovation projects (such as the

new terminal project at Lester B. Pearson International Airport) require much more

carefid planning and time. Ail of these factors directly affect cost, and the Iikelihood that

the cost may escalate as a result.

As much as factors within the project site boundaries affèct construction, so too does the

surrounding area and environrnent in which the project is buik The risk variables in this

category are listed in Table 3 -8.

Table 3.8: Location Risks

Beiief ~Venvork Analysis of Direcr Cosr Risk in Building Constn~tion 26

Ris k Foreign Purchased Goods Local Suitable Materials Suitable Equipment Availability Quaiified Local Labour Construction Support Facilities Locai Construction Market Availability of Energy Utilities Area Affluence

Source Stiglitz and Boadway 1994 CI1 1989, Laufer and Cohenca 1990 CI1 1989 Thomas and Napolitan 1995 CI1 1989 E x ~ e r t Interview CI1 t 989 CI1 1989 RandoI~h 1993

The affluence of the population of the surrounding area can affect attitudes and public

support for the project being built, Relevant public inquiries and hearings can be held up

indefinitely by citizens not in support of the construction. The affluence of the

population also affects the availability of construction support facilities such as housing

for labour and emergency medical services' as well as the presence of energy sources for

equipment.

Also important is the availability of locai labour and local equipment suitable for the

construction of the project. Laws of supply and demand dictate that greater availability

of goods or services reduce the cost of those goods and services. The availability of these

resources is greatly affected by the amount of other construction being done in the area as

compared to the capacity of contractors in the area.

3.3.8 ECONOMCC Rrs~s

There are two main types of risk variables in this category: performance of project

participants, and fiscal risks. Table 3.9 lists al1 of the risk variables in this category.

Table 3.9: Economic Risks

On occasion, contractors and suppliers to the project are unable to fulfill their obligations

Ris k Contractor Failure Subcontractor Failure Supplier FaiIure International Market Prices Construction Market Escalation Inflation Tax Rates Exchange Rates

to the project. The use of contractor prequalification processes has reduced the fiequency

- --

Source Flanagan and Norman 1993 Flanagan and Norman 1993 Flanagan and Norman 1993 StigIitz and Boadway 1 994 Widernan 1992 Stiglitz and Boadway 1994 CI1 1989 CI1 1989

Belief Nenvork .4naiysis of Direct Cost Risk in Building Consrrucrion 27

with which contractors on the project go out of business; however, insolvencies do occur.

U'hen they do, they can significantly impact project schedule and cost, not to mention the

fact that they may halt construction of the project altogether.

Fiscal factors that can affect the cost of construction projects are market escdation,

inflation, tax rates and exchange rates. These factors are al1 out of the control of the

project managers and project owners. As a result, they c m have a considerable impact on

final cost when they change in ways that are unexpected.

3.3.9 PO LITICAL RISKS

Politically related risk variables are generally out of the control of the project

participants. Table 3.10 lists the political nsk variables considered in this research.

Table 3.10: Political Risks

- - - - -- - -

Govemrnent stability and spending greatly affect the ainount of construction being done

Ris k Regulatory PenaIties Permits Required Government Spending on Construction Government

and consequently, market escalation and inflation. Government also influences

regulatory environments in which construction companies operate. Regulations and

permits are required on al1 construction projects, and if they are particularly stringent in a

Source Okpala and Aniekwu 1988, Wideman 1992 CI1 1989 CI1 1989, Stiglitz and Boadway 1994 CI1 1989. Stiolitz and Boadwav 1994

given jurisdiction, construction in that jurisdiction is more difficult to complete.

Belief Nenvork Analysis of Direct Cost Risk in Blrilding Constnrction 28

The rnost unpredictable and uncontrollable of risk variables on a construction project are

related to the environmental factors that are encountered. Project geology, altitude and

geology are factors of the physical environment that result in uncertainty in ground

conditions and the environmental sensitivity of a project site. In addition, natural

disasters such as mudslides or earthquakes are influenced by the ground conditions and

the prevailing geology of the area. Table 3.1 1 shows d l risk variables in this category.

Environmental Sensitivity 1 Flanagan and Norman 1993 II

Table 3.11: Environment Risks Ris k Ground Conditions

Source Flanagan and Norman 1993

Land-related natural disaster Weather Extremes Climate

The final major environmental factors that have an influence on project cost and schedule

Expert Interview CI1 1989, Thomas and Napolitan 1995 Mulholland and Christian 1999

Altitude Geology

are the weather and climate of the region. Both the ability to do work, and the

CaterpilIar 1997 CI1 1989, Cooper and Chapman 1987

productivity of labourers c m be reduced by inclement weather. The normal clirnate and

weather extremes such as hurricanes, tornadoes, ice storms, can seriously impede the

progress of a construction project.

3.4 R r s ~ LIST RANKTNG

Following compilation of al1 risk variables, the list of construction cost risk variables that

was compiled fiom the various sources was next ranked in such a way that only risk

variables lower on the list may have a causal effect on any particular risk. The reason

that the risk variables were ranked in this fashion is to aid in the construction of the belief

Belief :Ven~ork Analysis O/ Direct Cosr Risk in Building Constnrcfion 29

network; risk variables are drawn on to the network one at a time fiom the top of the list

to the bottom of the liste Connections may be drawn only fiom a newly entered variable

to those that are already on the model as appropriate. This is done to ensure that the

belief network model is acyclic (McCabe 1998).

To rank the lists from most dependent variable to most independent variable, a number of

intermediate steps were taken. First, each of the risk variables was grouped into one of

the ten main categories detailed in section 3.3. Afier the risk variables were categorized,

they were ranked within their groups. Literature was largely used in the ranking of these

lists, although some expert opinion was also solicited in the form of informa1 telephone

and persona1 interviews. Once the risk variables were ranked within their groups, the ten

groups were joined to create a master list. Note that the ten risk categories are ordered in

much the sarne way as the individual risk variables within the groups (groups lower on

the list in general affect groups higher on the list). This was done so that when the

groups were joined together, a master list of al1 risk variables would be formed that

followed the ranking rules. Some minor movement of risk variables between groups was

required following the joining of the groups, but on the whole the nsk variables were

correctly ordered. Table 3.12 is the result of the risk variable ranking.

Table 3.12: Ranked List of Construction Cost Risks

11 2. Labour Cost 1 Construction II 1

II 6. Cost Accounting 1 Management II

Construction Cost Risk Factor 1. Eouiornent Cost

3 . Material Cost 4. Construction daims 5. Overtime

11 7. Value Engineering ( Design II

Construction ContractuaVLegal Constmction

Ris k Ca tego ry Construction

Belief iVenvork Anaiysis of Direct Cost Risk in Btiriding Constmc~lon 30

1

I 8. Construction Delays 9. Failure delavs

Constmction Construction 1

Il 10. Contractor FaiIure ) Econornic 1 1. Subcontractor Failure 1 Economic 1 12. Supplier Failure 13. Labour productivity 14. Work OuantitY Deviations

Economic Constmction Construction

I I

11 22. Materials delivery 1 Management II

15. Material Shortage 16. Materia1 Waste

pp ---

19. Trade Coordination 20. Reaulatory PenaIties 2 1 - Long Work s t o ~ ~ a c e s

(1 23. Cooperative environment 1 Management II

Construction Construction

1 7. Design changes 18- Defective work

Management Political Management

11 24. International market mices 1 Economic II

Design Construction 1

. - -

25. Foreign purchased goods Location

II 27. Equiprnent productivity 28. SuitabIe eaui~ment availabilitv

11 31. Design Subrninal 1 Design II

26. LocaI suitable materials Location -1 -

29. MateriaV equiprnent Ioss 30- Labour Injuries/accidents 3 1. Qualified local labour 32. Ground Conditions 33. Archaeolozical Survev

Construction Location Constmction Construction Location EnvironrnentaI Construction

11 37. ~ u d g e t revkons 1 V

1 Owner II

1

I

11 4 1. Contractor payment type 1 ContractuaVLegal

3 5. Design Quality 36. Scorie Creen

38. Tenant Requirement Change 39. PM 40. Contract Clauses

Design Desion

Design Management Contractual/Leoal

42. PM work familiarity 43. PM knowledge of area 44. Construction/Ouerations Interference

Management Management Construction

-

45. Site security 46. Trafic congestion 47. Site access 48, Permits Reauired

11 53. Design team coordination 1 Design Il

-

Project Construction Project Political

-- --

49, Number of workers on site 50. Environmental sensitivity 5 1. Construction technology requirements 52. Corn~IexitY/ConstTUctabilitv of desion

~onstruct& Environmentai Construction Design

54. Qualified key PM personnel 55. Construction .sumort facilities

Management Location

56. Funding Source 57. Construction market escalation 58. Local construction market

Belief ;frenvork Anaiysis of Direcr C m Risk in Building Constnmion 3 1

Owner Economic Location -

59. Owner financial stabiiity 60. Physical project size 6 1. Competing activity on site

Owner Project Project

62. AvaiIability o f energy Location

64. Area affluence 65. Inflation

Location Economic

-- (1 7 1. Weather Extrernes 1 ~nvironmental 11

1 - -

68. Exchange Rates 69. Government 70. Land - related naturd disaster

1 63. Utilities

66. Government spending on construction 67. Tax Rates - - - . . - - . . . -

Econornic PoIitical Environmental

Location

Political Economic

72. CIirnate 73. Geo,gaphy

3.5 Rrs~ STATE DEFINITION

Afier ranking the risk variables to be used in the model from the most dependent variable

to most independent variable. the final task in the Risk Identification and Definition stage

of belief network Mode1 building is to define the states for every risk variable. Risk

states are the set of values that each variable may attain. The set of Risk states must be

mutually exclusive and collectively exhaustive. It must not be possible for any variable

to achieve more than one of its states at once, and the set of states must also include every

possible outcome that need to be uIcIuded in the model

Environmenta1 Environmental

74, AItitude 75. Geology

Nthough it is important to be diligent in coverïng a11 of the possible states, the greater the

number of variable states, the greater the nurnber of probabilities that must be elicited

f?om experts in later stages of mode1 development. Therefore, a balance must be struck

between completeness and overkill. To stnke that balance, an attempt was made to

ensure that each variable in the model is binary; that is. it has only two states. This may

introduce errors in accuracy. For example, consider the variable International Marker

l Environniental Environmental 1

Belief ~Venvork Analysis of Direct Cosr Risk in Building Construction 32

Relured Price Increases. The two states for Uris particular variable were "Greater than

expected" and "Less than or as expected". Zn truth? International Marker Related Price

lncrecrses can take on any value between -infïïty and +infiniS. To introduce the

number of states that would be required to be compIete wodd serve t o introduce

computational complexity that would make expert knowledge solicitation almost

impossible. For variables in which more states were absolutely necessary, more states

were added.

It is important to note, however, that extensive research into the best possible variable

states for each variable was not undertaken. Instead, the focus was to ensure that the

states for any given variable were mutually exclusive and exhaustive. Fwther research

needs to be conducted to better amve at the number of , and definition of, states for every

variable in the model.

3.6 DIvORCING VAWLES

A number of variables were added in the relationship identification process to reduce

computational complexity in the model. They are not shown in the original list of

variables as they were not part of the literature search process. These variabies and

descriptions of each will be discussed in Chapter Four: Relationship Identification.

3.7 PREDICTOR VARIABLES

As mentioned earlier, three variables were identified that are used to predict the final cost

of the project. The three variables are material cost, labour cost and equipment cost.

Beiief Nenvork Analysis oj' Direct Cosr Risk rn Binlding Consrrticrron 33

These three variables were found to have an impact on ten different building construction

cost centres. The new terminal project at Lester B. Pearson International Airport in

Toronto was used as an example project to provide the research with Spica1 construction

cost centres for large scaIe building projects. A total of IO cost centres were identified as

being represented by the three predictor variables. The cost centres are:

Substmcture Work (Excavation and B ackfill, Piling)

Structural Steel

Structural Concrete

Other Concrete (Concrete on Metal DecWSlab on Metd Deck)

Purchased, Prefabricated Construction Matenals (Precast Concrete,

Metal Deck, Miscellaneous Steel)

Roofing

~AC/Plumbing/EIectrical/Mechanical

Building Technical Systems/Comrnunications Systems/IT, Baggage

Handling, Security

Masonry, Carpentry

Finishings (Waterproofing/Fireproofing, Skylights, Doors, Ceilings,

Wall Finishes/Floor Finishes, Painting, Floorifig, Specialties, Window

Washing Systems, Fire Protection, Signs and Signage, Curtain wall,

Hardware, Glazing, Elevators/Escalators/Travelators, etc.)

Initially, these cost centres were to form the basis of the predictor variables. In effect, an

equipment cost, material cost, and labour cost variable was to be applied to each of these

cost centres. Following fùrther discussion with experts, it was determined that three

Belie f Nehrork Anabsis oj' Direct COSI Risk in Btrrlding Construction 34

macroscopic variables (Cost of Equiprnent, Casi of Labour, Cost of Materials) would

provide al1 of the accuracy required for a mode1 of this type. As a result, there are three

predictor variables used to assess the likelihood of various cost overruns in this research-

The next stage of research focuses on the determination of relationships between rïsk

variables.

Belzef Network Anaiysis of Direcf Cost Risk in Building Comnlcrion 35

Chapter Four: Relationship Identification

4.1 INTRODUCTION

The frrst step in the development of the belief network involved the identification of

factors that may affect the cost of a construction project - the nodes of the belief network

were identified. The second stage of belief network development involved the

identification of relationships between nsk variables, that is the connectors on the beIief

network. Two main methods were used in the relationship identification. They were:

0 Expert Swvey

Literature Search

Following each of these steps, an effort was made to reduce the cornplexity of the belief

network by eliminating nodes that had littie effect on the overall model, along with

eliminating direct connections between variables that could be made in other ways.

4.2 EXPERT SURVEY

A survey was developed to elicit expert opinion with regard to the identification of

relationships between risk variables. This survey was used to identie relationships that

were not documented in any available literature. A study on Schedule Risks in

Construction (Nasir 2000) used a similar survey to gain an understanding of how

schedule risk variables affect others. The same survey format was used in this research.

The 75 ranked schedule risks identified in the Iiteratwe search were listed down the side

of a 75x75 matrix, as well as across the bottom. The risk variables down the side of the

matrix represent causal variables (or parents) and the risk variables across the bottom

Beliefh'envork Analysis of Direct Cost Risk in Buildrng Consrnicrion 36

represent effect variables (children). AIso, as stated in Chapter Three, the nsk variables

were ranked so that no risk higher cn the list could have an effect on any Rsk Iower on

the list. Ranking the variables in this rnanner allowed the opportunity to eliminate one-

half of al1 the relationship pairs in the matrix (the upper-rïght half of the matrix was

composed of cause-effect relationships that were deemed impossible by virtue of the

ranking process.) This was a critical step; a 75x75 matrix would require the evaluation

of 5625 cause-effect pairs. Eliminating half of the relationships Iefi 28 13 relationships to

be studied. This, however, was still an unacceptable Iength. To furuier reduce the

number of cause-effect pairs to be analyzed in the survey, each pair was examined and

impossible causai variables were elirninated for each of the eBect variables in the survey.

This was done using expert interview with two experts, as well as literature wherever

possible. For example, it was determined that Site Sectrriiy would have such a negligible

or impossible effect on the Cost of labozcr that this particular pairing could be omitted

fiom the survey. The result of this process is a survey, a portion of which is shown in

Figure 4.1.

Grey-shaded areas are either impossible, or negligible. Unshaded boxes are relationships

that are possible; the experts were asked to make an assessrnent of the stren,& of these

relationships. The scoring system used by the experts was as follows:

O = causal risk has no effect on effect risk

1 = causal risk has a weak effect on effect risk

m 2 = causal risk has a significant effect on effect risk

r 3 = causal risk has a very strong effect on effect risk

Beliej~Venr.or.4 Anaiysis of Direct COSI Risk in Building Consinicrion 37

Fifteen experts were asked for survey opinions. Each expert was currently working as

part of the project management team at Pearson International Airport, but had previous

experience in a wide variety of different aspects of the building construction process. The

range of expert experience included individuals who had worked previously as

estirnators, daims evaluators, operations managers, and project upper management. Most

had worked on airport projects before, as well as other types of non-residential

construction. Experts were selected to ensure that survey group expertise was varied.

Surveys were conducted by distributing the questionnaires to the experts, explaining to

the group as a whole how the survey was to be filled out? and then being available for

questions over the phone or via e-mail. The experts were given a week to complete the

work. Nine experts responded to the request. The survey rnay be found in Appendix B.

i3eiief:Venvork i inalpis of Direct Cosr R d rn Biirlding Consrnrcrron 38

4.3 SURVEY RESULTS ANALYSIS

After the experts completed the surveys and retumed hem, the next step was to use those

results to determine which relationships should be included in the beiief network. This

required a consistent set of niles to analyze the colIection of responses. This research

used a set of rules similar to that used in the analysis of schedule risk research (Nasir,

2000). A two-tiered approach was used. The f ~ s t step was to eliminate al1 relationships

that received results that strongly suggested the experts felt there was no significant

cause-effect relationship; rejection tests were used for this purpose. Second, the

rernaining relationships had to pass one of severd acceptance tests that indicate a

significant relationship. Cause-effect pairs that did not fail any of the rejection tests, and

passed at least one of the acceptance tests were deemed to be valid pairs that should be

incIuded in the model. The elimination and acceptance tests used in the construction of

the model are shown in Tables 4.1 and 4.2.

Survey Rejection tests Result

Table 4.1: Relationshil

No Relationship No Relationship

1

No Relationship

Condition

Average score < 1 .O 1 Average score < 1.5 and weak scores (Os, 1s) outnumber strong scores (2s, 3s) Average score < 1.5 and data skewness positive

(1 Average score > 1.99 1 Relationship

Table 4.2: Relationship Survey Acceptance Tests Condition

11 No zeroes in survev result set 1 Relationship

Result

Average score > 1.49 and strong scores (2s, 3s) outnumber weak scores (Os, 1s) Average score > 1.49 and skewness negative or zero

Belief Xenvork .4nalysis oJDirecr Cos1 Risk in Building Cons~ruc~ion 39

Reiationship

Relationship

Skewness characterizes the degree of asymmetry of a distribution about its mean. In

sirnpler tems, it measures whether the Ionger tail of the statistical distribution lies to the

positive or negative side of the mean. If the Ionger tail is to the Ieft (Le. negative) side of

the mean, then more of the data is grouped around higher values; the skewness is said to

be negative, and vice versa. Skewness is important to this analysis because it helps to

determine whether the survey results are "Ieaning" toward values that indicate acceptable

relationships.

Of the 452 relationships analyzed in the s w e y . 171 were accepted by the experts, 28 1

were rejected. Appendix C shows the distribution of the number of responses for each

score, for each parent-child combination sweyed. The number of Os, ls, 2s, and 3s are

shown,

These tests are, in general, more inclusive than the schedule risk tests (Nasir, 2000). As a

result, 58 additional cause-effect pairs were accepted in this research that would have

been rejected by the scheduie research criteria. Each of these 58 "borderline

relationships" were discussed with tcvo experts to determine which should be included,

and which should not be included in the model. Table 4.3 is a list of borderline

relationships that passed the criteria in this research, but were rejected as a result of

expert review.

Belief ~Venvork ..lnalysis oJDirecr Cosr Ruk in Building Cansrnlcrron 40

Following the expert survey. a Iiterature search was conducted to detemine if there were

reIationships that existed that were not identified as a resuft of the expert survey. Results

of the similar schedule risk (Nasir, 2000) research were used, as were the sources from

the risk identification literature search. Table 4.4 shows parent-child (cause-effect)

relationships that were identified as a result of this effort.

Table 4.3: Borderline Relationships eliminated as a result of expert analysis l 1

Parent Variable 1. Site AccessEgress 2. Land related naturai disaster

Chiid VariabIe Site Security Availabilitv of enerm

3 - Construction market escalation 4. Work Quan:ity Deviations 5. Work Quantity Deviations 6- MaterialfEquiprnent LossKlarnage 7. Owner Financial Stability 8. Subcontractor FaiIure

Budget revisions allowed Construction Clairns Construction Delays Construction Delays Contract Clauses Contractor FaiIure

9. PM ~ b i l i t y / W i G ~ n e s s to meet obligations 10. PM Familiarity with type of work I 1. Ground Conditions 12. Construction Market Escalation

17. Geology 1 Work Quantity Deviations

- -

rade Coordination Trade Coordination Equipment Cost Labour Cost

1 13. MaterialEquipment Loss/Damage ' 14. Design Changes 1 15. Geology

1 6. Budget Revisions Allowed

Material Cost Defective Work Design Changes Work Quantity Deviations

18- Presence/location of utilities 19. Stabilitv/so~histication of zovernment

Equiprnent productivity Exchanoe rates

20- Complexity/Constnictability of Design 2 1. Weather Extrernes 22. StabilitylSophistication of Govemment

- --

26- Design Quality 1 Design Tirneliness

Labour Productivity Land related naturaI disaster Permits required

23- Altitude 24. Qualified Key PM Personnel 25. Sumlier Failure

Weather Extrernes PM Farniliarity with type of work Subcontractor failure

27. Weather Extremes 28. Land Related NaturaI Disaster 29. Long Work Stoppages

Only 18 additional relationships were identified in the literatwe study, but these

Overtirne Environmental Sensitivity Labour Productivity

30. Ground Conditions 3 1. Environmenta1 Sensitivity

relationships added to the completeness of the overall model. Also of note are the

Labour Productiviv Labour Productivity

BefcefrVehvork Anaipis of Direct Cost Rrsk in Building Construcfion 41

variables that appear in Table 4.4 that.were not part of the original list of risk variables

developed in the Risk Identification step, or present in the expert survey. These extra

variables were added as part of the Divorcing process originally introduced in Chapter

Three. The reason that these relationships were not identified in the expert survey is that

the literature search to identiQ relationships occurred afier the survey results were

identified. To ensure model completeness, these relationships were added.

In some cases, risk variables were found to have a large number of parent variables. The

Table 4.4: Variable Relationships identified in Literature Study

nurnber of required probabilities of a single chiid variable increases exponentially with

Parent Variable 1, Climate 2. Labour Injuries/Accidents 3 J - Project Material Shortage 4. Suitable Equipment Availability 5. Number of Workers on Site 6. Trafic Congestion on Site 7. Construction Technology Requirements 8. Design Changes 9. Defective Work IO. Design Changes I I . MateriaEquipment Loss Darnage 12, Materials Delivery Prompmess 13 - Material Waste 14. Altitude 15. Materiais/Equiprnent LossiDamage IO. Archaeological Survey 17. Construction Technology Requirements 18- Project Material Shortage

the addition of a single parent variable. A child with 2 parents and each parent with 2

Child Variable Short Breaks Short Breaks Short Breaks Short Breaks Labour Congestion Labour Congestion Labour Understanding of Design Work Quantity Deviations Work Quantity Deviations Project Material Shortage Project Material Shortage Project Materia1 S hortage Project Material Shortage Equipment Productivity Suitable Equipment Availability Ground Conditions Design Quality Cost of Materials

states requires the determination of 22 = 4 probabilities; the sarne child with 5 parents

requires 23 = 32 probabilities (it is a 2" relationship). In this model, there were three

variables (construction claims, construction delays, labour productivity) with at least ten

Belief 'Venvork Analysis of Direct Cost Risk in Building Cornlaion 42

parents. These three variables done would have required the solicitation of 68608

probabilities eom experts in the relationship quantification stage of research - more Sian

the other 72 variables combined,

A technique called "Divorcing" (Jensen, 1996) was used to reduce the number of

probabilities required in the relationship quantification stage, and the number of

calculations required once the mode1 was complete. Divorcing involves the introduction

of "intermediate" variables that are placed on the network between the existing parent

and child variables. Introduction of these intermediate variables reduces the exponential

effect of having a Large number of parents.

The Constrz(cfion CIaims variable, for example, had 12 parents. Without divorcing, there

would have been 4096 cornbinations of parent states to examine. Following divorcing,

54 different cornbinations needed to be studied.

Available Qzralzfied key PM

Personnel

PM A b ility/WiZZingness to meet

o bligarions

Tenant Requirement Change

Design Changes

Scope Creep

Design Tirneliness

Constrzrctio n De Zays

Overtime

Long Work Stoppages

Defective Work

Grotrnd Conditions

Trade Co ordination

Prior to divorcing, the twelve parents of the Tonstniction Claims" variable were:

Belie/iVenvork linalysis of Direct Cosf Risk in Building Consrnrcrion 43

Divorcing the Construction Claims node involved

variables. The four intermediate variables were:

Design Related CZuims

Delay Reluted Claims

Field Reluted Claims

PMAbiMyto MitigateClairns

the addition of four intermediate

Each of the original 12 parent variables was assigned as the parent of one of these

intermediate variables. The original parent variable Sius becarne "Grandparents" to the

Constrzrction CZaims variable. Table 4.5 shows how each original parent variable was

assigned.

Table 4.5: Divorcine the Construction Claims Variable - New Construction Claims Parent Variable Design Claims

Delay Clairns

Original Parent Variable; Construction CIaims "Grandparent Variable" Design Changes Scope Creep Design Subrnittal Tenant Reauirement Change

Construction Delays Overtime Long Work Stoppages l

Field Clairns Trade Coordination Ground Conditions

l

As a result of this divorcing process, 8 probabilities were collected for each of the D e l q

Claims and Field Cluims variables, 16 for the Design Clciirns node, while 4 probabilities

/

need to be collected for the PM ability to mitigate claims variable. In addition, since the

Defective Work

PM Ability to Mitigate Clairni I

Qualified key PM personnel PM

four intermediate variables are now the only parents of the Construction Claim variable,

I

16 more probabilities were collected for a total of 52. Belief ~Venvork Analysis of Direct Cost Risk in Building Consrnrcrion 44

The Conslruction Delays and Labour Productivity variables were divorced in a sirnilar

manner. Details are found in Appendix D. The appendix shows divorced configurations

of parent variables for each of the three divorced variables in the model. Figure 4.3

shows an example of what is found in Appendix D. Figure 4.2 shows the original

Constrziction Claims configuration. Figure 4.3 shows the divorced situation.

Figure 4.2: Non-divorced Construction CInims Variable

Figure 4.3: Divorced Ctmstruction Chims Variable

Belief h'envork Anaiysis of Direcr Cost Ri& in Btrilding Consrnrcrion 45

4.6 DATA REDUCTION

Following the determination of valid relationships for the belief network model, and the

divorcing process for three of the variables, it was important to further reduce the

computational complexity of the rnodel (Sarkar and Murthy 1996). Each of the

modifications invoIved the elimination of either a risk factor, or a variable connector. A

description of each of the modifications follows. Further information may be found in

Appendix K.

4.6.1 RELATIONSHIP ELIMINATION: TENANTREQUIREMENT CHANGE-DESIGN CLAIMS

The Design CZciirns node was introduced as a divorcing variable for Constrzrction CZaims.

Originally, it had four parents. They were:

Design Changes

Scope Creep

Design Timeliness

Tenant Requirernenr Change

Tenant Requirement Change, however, is a parent of Scope Creep. It was determined

that the Tenant Requirement Change variable would influence the Design Clnirns

variable through this mitigating variable (Tenant Reqzrirernenr Change remains as a

"grandparent", so to speak). As such, the connection between Tenant Requirement

Change and Design CZaims was removed.

BelieJNenvork Anolysis of Direct Cosr Risk in Building Consfnrction 46

4.6.2 R~ZLATIONSHIP ELIMINATION: QUALIFIED LOCAL LABOUR-LABOUR DELA YS

Labour Delays is a node that was introduced as a result of the divorcing process

involving the Constrzïction DeZays variable. Original parents of the Labozïr DeZays

variable were:

Labour Productivity

QuaZzFed Local Labour

Defective Work

Long WorkStoppages

Trade Coordination

QunlzJied Local Labour is a parent of both Lubozïr Prodzïctivity and Defective Work. As

a result, it affects Labour Delays as a grandparent through these two variables, and the

QzmIz@ed Local Labour - Labozïr DeZays connection was rernoved.

Original parents of the Project Materid Shortage variable were:

Local Szïitable Materials

Design Changes

Materiuls Delivery Promptness

Materiul Waste

Local Suirable Materiuls, a parent of iMateria1.s Delivery Prompfness is therefore a

grandparent of Project Material Shortage. As a result, the Local Szritable Materials -

Project Material Shortage pair was eliminated.

Bekf Nenvork Analysis o j Direcf Cosl Ruk in Brtilding Consrrucrion 47

Tenant Requirement Change is a parent of Scope Creep, which is also a parent of Design

Changes. As a result, it was determined that Tenanr Reqtrirement Change would affect

Design Changes through &ope Creep. The Tenant Requirement Change - Design

Change comection was therefore elirninated

Design Team Coordination is a parent of Scope Creep, which is also a parent of Design

Changes. As a result, the connection between Design Team Coordinafion and Design

Changes was eliminated because it was determined that Design Team Coordinarion had

influence through Scope Creep.

4.7 MODEL STRUCTURE

A nurnber of techniques, including Divorcing, Risk EIimination and Relationship

Elimination were used to minimize the nwnber of connections on the belief network

model. These techniques were employed in such a way that the completeness of the

rnodel was not compromised. Risk variables were eliminated only when they had little

impact. Relationships were elirninated only when the original parent variable maintained

an influence over the child in a "grandparent" role. The resulting rnodel has 87 variables

(including added divorcing variables and 3 predictor variables), and 152 connections

(including 134 risk connections and 18 connections to predictor variables).

BeiieJNenvork AnaIysis of' Direcl Cost Risk in Building Consrnrction 48

Figure 4.4 shows a completed diagram of the entire beIief network model. It is difficult

to discern each of the nodes and connections by Looking at the chart itself; a table with

each child variable, dong with respective parent variables, variable definitions and

variable States rnay be found in Appendix A.

Bslief Nenvork Analysis of Direct Cost Risk in BzrilâÏng Constnlc~ion 49

Chapter Five: Probability Determination

5.1 INTRODUCTION

Following the identification of relationships between risk variables, conditionai

probabiIities for every node were determined for each parent state combination. Expert

survey was used to determine these probabilities. This was quite a long and involved

task, and steps taken to reduce the extent of this exercise were documented in the

previous chapter (relationship elimination, risk elimination). In this chapter, three

additional swey-reducing techniques are detailed. Also, the steps taken to determine

each of the conditional probabilities required are also discussed.

5.2 DATA REDUCTION

There are 87 variables, 153 variable connections on the cornpleted model. As a result,

there are 493 conditional probabilities required for connections behveen risk variables,

1568 required for connections to predictor variables. Clearly an effort was required to

reduce the nurnber of probabilities that were to be determined by expert survey. Three

main techniques were used in order to accomplish this goal. They were:

@ Asymrnetric Assessrnent

@ Parent State Ranking

8 Probability Cuve Development

Each of these three techniques wiil now be discussed in turn.

Belief Nenvork Anaiysis of DÏrect Cost Risk in Building Cons!nrcrion 5 1

5.2-1 ASYMMETRIC ASSESSMENT

Asymmetrk Assessment is a technique used to eliminate parent state combinations that

either do not make sense, or are dominated by a subset of the parent state variables,

Figure 5.1 shows an exarnple of a variable that was asyrnmetrically assessed. A shortage

of materiais on site is a critical factor that can put a project behind schedule. Parent

variables of the Muterid Shortage variable are Design Changes, Murerial/Equipmenr

Loss/Damage, Materials Dehery Prornptness. and Mulerial Waste. Most importantl y,

however is the delivery of materiais to the site. Without materiais on site, no arnount of

design changes, materials loss or darnage, or material waste matter. In effect, the

Materials DeZivery Promptness dominates the three variables when its state is "frequently

Iate".

Frequently Late Generally on time

b ~ a t e r i a l Waste

ateriaVEquipment Loss

sign Changes Maior Minor or no or no sign Changes M aior Minor or no

MateriaVEquipment Loss Major

Design Changes m ~ a i o r F=

Figure 5.1: Asymrnetric Assessment structure for Project MaterialS/'ortage

The "generally on time" state of the Mderiuls DeZivery variable is not dominant. As a

result, al1 of the other combinations of the other parent variables must be considered. On

Relief rVenvot-k Analysis of Direct Cosl Risk in Bt~ilding Constnrction 52

the other hand, when materials are kequently delivered late to the site, the other parent

variables need not be considered. The portion of the asymmetric assessment as shown

above reflects this fact,

In this model, the following variables were asyrnmetrically assessed:

Cons&rzrction Delays

* Work Qzlantity Deviations

Project Material Shortage

O Sztitable Equipment AvaiZab iZi@

TI-afic Congestion on Sire

Asymrnetric Assessrnent structures for al1 of the above variables may be found in

Appendix E. The structures of the Asymmetnc Assessrnents in Appendix F are as shown

in Figure 5.1. Probabilities are required for each of the termination points in the

structure. In Figure 5.1, for example, the "Major" and "Minor or no" States of Design

Changes are termination points, and require that probabilities be surveyed.

The benefit of asymmetrically assessing variables is clear from studying the structure of

the Mntei-id Shortage variable asymmetric assessrnent. In this case, only nine parent

state combinations need conditional probabilities attached to them. Without asymmetric

assessment, 16 probabilities would need to be determined. Not only does this accomplish

shortening the expert survey, but it seemed as though the survey was easier for the expert

to handle with fewer probabilities to assess for a single variable. That is, trying to

differentiate between parent state combinations when there are 16 such combinations is

Eleliej~Venvork Rnalysts of Direct Cosr Risk in Bzrrlding Consfnrcfion 53

much more difficult than if there are only 9 combinations. Asymmetnc Assessrnent

reduced the effort required from experts.

5.2.2 PARENT STATE COMB~NATION ~ N W N G

Another technique used to reduce the effort required from experts was tested on a limited

basis in this study. Parent state cornbinations for every variable were ranked after careful

analysis from highest likelihood to lowest Iikelihood of causing a negative impact on the

child variable. An exarnple of this is shown in Figure 5.2. This was done in an attempt,

again, to reduce the effort required from the experts.

In Figure 5.2, the first colurnn is an identification number. The second column shows the

combination of parents and parent States. The last colurnn in the table shows the child

variable, and child state.

In addition to this ranking of al1 variables, some variables that had a large number of

parent state combinations were subject to an alternative method of surveying. Instead of

asking al1 experts to attach a probability to every combination, one of the three experts

was asked to reply to only every third or fourth combination. Probabilities in between

surveyed combinations were interpolated using the regression tool in Microsofi Excel.

Regression analysis is used to minimize the sum of the differences between predicted and

actual values. Each of the five trend-line regression tools (linear, logarithmic, 2"d degree

polynomial, power and exponential) were tested for each of the variables surveyed in this

manner. The regression that produced the R-squared value closest to 1 (the best fit) was

Belief :tlenvork Anafysis o/ Direcl Cost Risk in Building Consrnrcrion 54

chosen to interpolate the data not surveyed- Important to note is the fact that the values

given by the experts were used (Le, the regression curve vaIues for parent state

combinations replied to in the survey were not used). Again, this resulted in fewer

questions being asked of the expert, and a faster survey completion tirne.

ID# Parent Variable and State ChiId Variable. state 6 1 I ~ a j o r Construction DeIays Vif i l 1 Result in

l ~ o r s e than Expected Labour Productivity

l ~ r e s e n c e of Scope Creep

I --

Construction Delays Wi l l Result in *expected Overtime o or se than Expected Labour Pmductivity

-

3 Major Construction Delays Wi l l Resul t in -expected Overtime

IAS expected o r better Labour Productivity

4 Major Construction Delays WiII Result in ,expected Overtim e

(AS expected or better Labour Productivity

5 Minor o r no Construction Delays Wi l l Result in expected Overtirne


l ~ r e s e n c e of Scope Creep

Wil l Result in zexpected Overtime I 6 Minor or no Construction Delays


No Scope Creep

Wil l Result in >.expected Ovenime e --

7 I ~ i n o r o r ni Construction Delays

[AS expected or bttter Labour Pmductivity

I ~ r e s e n c e o f Scope Creep r

Wil l Result in >expected Overtirne I 8 Minor or no Construction Delays

IAS expected or better Labour Productivity

!NO Scope Creep

Figure 5 i: Ranking from severe conditions least severe conditions, Overfime child variable

The variabIes swveyed in this manner were:

Suirable Equipment Availnbiliy

Work Quantiiy Deviafions

Labour Productivity

Belie/Nenrork Analysis of Direct Cos1 Risk in Building Constnrc~ion 55

Table 5.1 shows the child variable, regression c u v e used, regression equation, and

corresponding R-squared value.

Table 5.1: Regression of Parent State-interpoiated variables

- - --

As shown above, the R-squared values are certaidy reasonable. The curves fit the

Availability Work Quantity Deviations Labow Productivity

surveyed data relatively well. In addition, when the interpolated values were compared

R-squared 0.67

Child Variable Suitable Equipment

to the values surveyed Erom the other two experts that answered the same questions, they

Exponential

2nd Degree Po lvnomial

were found to be quite similar.

Regression Type Logarithmic

Table 5.2 is an exarnple cornparison for the Labozrr Procizrctivity variable. The difference

between the interpolated value and the two sux-veyed values is shown as well. As c m be

seen, the difference between surveyed and interpolated values is relatively small, and

acceptable given the precision of this survey (it will be explained later that surveyed

values are acceptable if they were within 20% of the average).

Regression Equation y=- 16.7Inxt80-3

Y=92.1 exp(-0.123 7x)

y=-0.2 1 x'-0.57x+9 1.1

Experts 2 and 9 were surveyed for a11 of the parent state combinations. Expert 7 was

surveyed only for rankings 1, 5, 9, 13 and 16. The other values for Expert 7 were

interpolated.

0.59

0.73

Belief A'envork rinalysrs of Direct Cosr Risk in Building Consrntcrion 56

Cornparisons simiIar to that offered in Table 5.2 for the other two variables surveyed in

this manner may be found in Appendix F. Shown in the appendk is the chart format as

in Table 5.2, as well as the regression graph that corresponds to the analysis.

Average Differenix 1 8-2 12.7 7.0 1

Table 5.2: Difference befween interpolated values and surveyed values

%le not used extensively in this research, this technique sped up the survey process.

14 15 16

and reduced the effort required fiom the expert. It merits further attention in fi~ture

studies. The experts that were surveyed in this manner were quite receptive to this

60 50 30

method, and were thankful that survey time was reduced. The method did take a bit of

explmation, but once they understood what they were doing. they proceeded through the

40 40 20

questions quite quickly.

5.2.3 PROBABILITY CURVE DEVELOP~MENT

As srated in the begiming of this chapter, 1568 probabilities are required for the

40 30 30

connections to the predictor variables (muterid cost, labotir cos[, equiprnent cost). It

would take months to survey experts for these probabilities. As a result, this method was

46.7 40.0 26.7

Belief Xehvork Analysis of Direct Cosr Risk in Building Consrrucrion 57

-20 -2 0 nia

O 10 nia

-6-7 0.0 nia

not used. Instead, normal probability curves were developed to produce the probabilities

required for these predictor variables. Two main steps were required. First, parent state

combinations needed to be ranked. Second, normal curves were produced that assigned

probabilities to each child state, based on a corresponding parent state combination-

5.2.3.1 PROBABILITY CURVE PARENT STATE M N K I N G

The firsr step in using the probability curves kvas to rank the parent state combinations

from worst-case scenario to best-case scenario. Ranking was done by refemng to the

strengths attached to each relationship by the relationship identification expert survey

conducted in Chapter Four. For example, the Equiprnenf Cost predictor variable has six

parents. They are:

Szritable Equipment AvaiZubility

Equiprnent Productivity

Construction Market Escalcit ion

Inflar io n

Construc t ion Clairns

Value Engineering

In the relationship identification survey. experts were asked to judge the strengrh of the

relationship between each of these variables and Equipmenf Cost variables on a scale of

zero to three, A score of zero meant there was no relationship; a score of three meant a

very strong relationship. The average score returned by a survey of nine experts was

used to rank the parent combinations in t h i s stage of the relationship quantification.

Belief Nenvork Anolysis of Direcl Cost Risk in Bziilciing Consrnrcfion 58

Table 5.3 shows the strength of effect of each of the Equipment Cost parent variables on

the child variable.

Note that the final two parent variables, Construction Claims and Value Engineering

were not identified as parents by the expert survey. They were identified as part of the

Iiterature search. As a result, they were given the minimum score required to quali@ as

parents, 1.5. This minimum score is denved fiom the relationship rejection and

acceptance mies discussed in section 4.3 (Tables 4.1 and 4.2 detail these rules).

Table 5.3: Strength of parent variables on "Equipment Cost" predictor variable

1) Construction Claims 1 1.5 II

Equipment Cost Parent Variable

Suitable Equipment Availability Equipment Productivity Construction Market Escalation Inflation

[I Value Engineering 1 1.5

Strength of Parent-ChiId Relationship

2.22 1.67 1.78 1.75

When the parent variable assumed a "negative" or worst-case state, a score equal to the

strength of relationship was assigned to the parent variable combination ranking. For

example, if Suituble Equipment -4vaiZabil-y assumed the "Insufficient" state, a score of

2.22 was added to the score for that particular ranking. Table 5.4 shows an exarnple

parent state combination, and the total score used to rank that combination.

Belief Nenvork Analysis of Direcl Cosr Risk in Btrilding Constnrction 59

Table 5.4: Example ranking calculation Variable Suitable Equipment Availability Equipment P roductivity Construction Market Escalation Inflation Construction Claims Value Engineering

State Insuffkient >= Expected <= Expected > Expected

Major Practiced

Score 2-23 (negative state)

O (positive state) O (positive state)

1 -75 (negative state) 1.5 (negative state)

O (positive state) Sum: 5.47 -

Afier every possible parent state combination was scored, they were ranked from highest

score (worst-case scenarïo) to lowest score (best-case scenarïo),

5.2.3.2 PROBABILITY CURVES

The probability curves were developed assuming 16 ranked combinations of parent state

variables. ln fact, there are no predictor variables with just 16 combinations (each had

either 64 combinations or 96 combinations). On the other hand, to develop curves with

96 separate rankings would irnply that there was approximately 1% difference between

consecutive combinations. There is no way that such a minute difference could be

justified or explained. As a result, the combinations were divided into groups based on

the strength of their effect on the child variable. Combinations that had similar stren,@hs

of effect were grouped together.

Each predictor variable has eight different states (+Ils%. +95%, +75%, +55%, +35%,

l5%, -5%, -25% of budget). Eight normal curves, or distributions. were therefore

needed. The curve means were spaced evenly over the 16 rankings on the x-axis of the

probability c u v e graph. The y-axis of the graph represented the probability associated

with a given curve for a given ranking. To space the curves evenly over the 16 rankings,

the mean of each normal curve was spaced at regular intervals over the rankings on the x-

axis (the probability curve means were 1 .O, 3.14, 5.28, 7.42, 9.56, 1 1.7, 13.84, 16.0 -

spaced every 2 1/7 rankings).

Belief Nencork .4nalysrs of Direct Cosr R ~ s k in Building Consrnrcmn 60

The other data required to produce a normal c w e is the standard deviation. There is no

documented systematic method to select the standard deviation. So, a nwnber of curves

were developed, and the construction experts were asked to select the c w e that they

believed represented actual occurrences most accurately. In the final analysis, curves

with a standard deviation of 2.5 were selected. Eight curves with standard deviation 2.5,

and means 1 .O, 3.14, 5.28, 7.42, 9.56, 1 1 -7, 13 -84, 16.0 were developed. These curves

are show in Figure 5.3.

8 Child States, 16 Parent State Cornbinations, Standard Deviation = 2.5

0.600 --

1 2 3 4 5 6 7 8 9 1 0 1 1 1 2 1 3 1 4 1 5 1 6

Parent Pmbability Combination Ranking

Figure 5.3: Probability curves for Predictor variables

Each curve represents one child state. As c m be seen, for the #1 ranking (worst-case

scenario), the probabiIity of a 1 15% increase in cost over the budget is 5 1%, the

likelihood of an 95% increase is 35%, 75% increase - 11% and so on. For the second

worst case scenario, the probabilities are slightly different. As the probability of one state

Belief Nenvork rinolysrs of Direcr Cosr Risk in Building Construcrion 61

occurring increases, the others rnust decrease, and this graph represents this fact - the

surn of al1 probabilities for each parent state ranking is 1.0.

Appendix G has a chart with the raw data used to produce these curves. Table 5.5 is a

sarnple of what may be found in Appendix G.

-- ----

In Table 5.5, the top row (containing percentages fiom H 1 5 % to -25%) shows the

appropriate state of the predictor variable- The second row shows the rnean of the cuve

corresponding to the predictor variable state shown in the row above. The "StdDev" row

simpIy shows that the standard deviation for each of the curves is 2.5. The values shown

in the chart (1.0, 2.0, 3.0) are the values corresponding to the parent probability

combination ranking (1 .O = worst-case parent state combination). FinaIIy, the values,

ranging fiom 0.5 10 d o m to 0.000, are probabilities used in the model.

In the case of the Eqzuprnent Cos? variables, the Iowest ranking score (as discussed earlier

in this section) was 0, and the highest score kvas 10.42. These scores were multiplied by

a value that produced a range of scores from 0-1 6 (in this case l6/lO.42 = 1 -54). Scores

between 0-0.99 were assigned the best-case probabilities fiom the probability curve

(ranking l), scores between 1-1.99 were assigned the second best-case probabilities

(ranking 2), scores between 15-16 were assigned the worst case ranking (ranking 16) and

so forth. Appendix H shows each parent state combination for each predictor variable,

BelieJh'envork rlnalysis of Direct Cosr Risk in Building Consrrucfion 62

along with its ranking and score. Table 5.6 shows a sample of the Equipment Cost

ranking .

The chart shows the appropriate parent state combination, along with the determined

score and ranking. In the parent variable row, the parent variabIe name, as well as the

weight of the parent variable are shown.

Table 5.6: Appendix H Sample Sauioment Cost Variable Parent State Rankinq

Parent Variables: Suitable Equiprnent Availabilit-j Inflation Value Engineering Construetmn Market Escalation Equipment PmductMty Construction Claims

5.2.3.3 DIVORCING CURVES

In addition to being used for the predictor variables, the same probability cuves

(standard deviation = 2.5, evenly spaced means) were used for divorced variables. It did

not make much sense to ask experts to answer questions about variables that were

manufactured. As a result, the added variables were ranked according to the strength of

their parent variable's effect on the divorced variable. This ranking is shown in

Appendix J. The strength of these relationships was based on the values returned by

expert in the relationship identification matrix survey, in a manner similar to that

performed on predictor variables (depicted in Table 5.6).

Vanable nvndabstv ~ 2 . 2 ~ ) ~ o ~ e t i v d y ( t rn ~ a r k e t &.wan(~ 78)

State: insuriment m e Quected >=Expec!ed ~Erptded d3pcded *Exgtcted 1 mm M- rn ~sdired ~rsctised Score

Belief Nenvork Anaiysis of Direct Cosr Risk in Building Constnrction 63

4 3

1

X X X X X X

X X X X

X X X

X

X

X X X X X

X X X

X X X X

X

X X X X

X x 1

* X I

X X X X X

X

8.M 8-64 8.W 8.75 8.92

X

12.59 13.27 13.31 13.44 13.70

8.92 10.42

13.70 16.00

5.3 PROBABILITY EXPERT SURVEY

5.3.1 EXPERT SURVEY DEVELOPMENT

After reducing the number of probabilities required to be solicited from experts, an expert

survey was developed to collect the remainder of the probabilities required for the belief

network model. A survey was used because there was essentially no literature on the

topic of conditional probabilities between the parents and child variables in this model.

The expert survey was the only option for detennining these probabilities.

As stated earlier, the parent state combinations for al1 variables were ranked as much as

possible to reflect a worst-case scenario to best-case scenario progression. This was done

to aid the experts and decrease the time required to survey each expert. Nine experts

were surveyed, but each expert only answered about one third of the questions on the

survey. The experts were asked questions that, as much as possible, were related to their

area of expertise. Table 5.7 is a chart that details which expert answered which question.

Table 5.7: Division of auestions on the ~robabiiitv survev Expert Expert 1 Expert 2

II Expert 9 1 1.7.8.15.19.25.28-30.35.36.42.46.51.52.54.56.58 II

-- -- - - - -- -

Questions ~nswered 6,8,28,32-34,41 ,43-46,48,507S 134 l,l5,25,26,3 5,4 1 -44,47

Expert 3 Expert 4 Expert 5 Expert 6 Expert 7

-- - -

The survey had a column with state combinations for each parent variable, a column with

the child variable and its state, and a column with the numbers 1, 10, 20, 30, 40, 50, 60,

70, 80, 90, 100 (the numbers represented the conditional probability attached to the

Beliej.?envork Analysis o j Direct Cost Risk in Building Constnrcrion 64

19,20-22,24,26,27,3 1,47,53,55,57 23,29,30,36-40,42,45,46,49,5 1 ,53-55,57,58 6,20-S2,24,X727,3 1 -34,48 6-8,19,23,26,28,37-39,41,43-45,47,49,50,56 lS,20-22,24,27,3 1 -3S748,5O,53

relationship for the given parent state combination). Each expert was asked to study the

parent variables and their States, the child variable and its state, and assign a conditional

probability based on their experience. Three experts answered each question, Figure 5.4

shows part of the relationship quantification survey. Note that, in addition to the

quantitative response asked of the experts, a qualitative guideline was added to the survey

in the form of descriptions (Strongly Agree, Agree, In Between, Disagree, Strongly

Disagree) at the top of each page. The experts were asked to consider these qualitative

descriptions in their assessment of each conditional probability.

Each expert took approximately 30-45 minutes to complete the survey. No expert

seerned burdened with a survey of this length. The author sat with each expert during the

cornpletion of the sunrey to ensure that any questions could be answered promptly, and to

ensure the expert was not confused by the definitions of variables or their relationships to

one another. The structwed interview technique worked quite effectively in this instance

as well- In addition to these conditional probabilities collected, 23 variables had no

parents, and prior probabilities were collected by either survey or literature search.

Belief Nenvork Analys O/ Direcf Cosf Risk in Birilàing Consfruaion 65

5.3.2 SURVEY DATA ANALYSIS

Following collection of expert opinion during the sunreying process, al1 of the surveys

were combined into one master survey of d l variables with parent state combinations and

IDU

23 t

2

1

4

5

6

7

8

respective probabilities. Current research being conducted at the University of Toronto

suggests that in large network models such as this one, variables are only significantly

sensitive to changes greater than 20% in other network variables. As a result, the average

of three surveyed experts was used, except when one or more of the expert opinions

Figure 5.4: Sample Probability Survey

Car*

P o a OtsignQwEty Resmct ot k a p e Cl-p Complu CoapkdtyiConztncnbiEtp cd 0.:;9n

Good O ~ O u a ü t y Piesencc of Seope û n p Complu bmpluiqlCo.structrb*ry d OcGgr,

Poor OssiqnQdity P t a u c r ot k o p c Cr«p % d n c Cornplcitqi~on+t~~iabiuty of Dtriqn

Poor OcsignQurEty No tcopt Ocrp Conples Conpl&tqtCam~tncnbiEty of Oeiqn

G a d Oeign t&aEty Rez incr of k o p r Crep R o u t k CnnplePty4Colrtru~hb*h, of O ~ i q n

Good OcignQuaüty No k o p e û n p Conplex Compl~tylConstmc1a~1t~ d Oti-

Poar Design Qualttp No Scopc Weep Routine ConvluitvlCoasu~cabairy d 0e:ign

t o o d n~+a~dw No S a p e Clcep Routine Compl~itylCactm~tabiiily of O a q n

varied by more than 20% fiom the average. In this case, the expert was revisited and

asked if they would consider revising their response given a more complete expianation

W r d h

W l r ~ z t i n

M r d t i n

of the parent variables and parent variable States. This was done until al1 responses were

in the i 20% range. In a minority of the cases, the average was not used; a value was

fffect

M a + CeigaChange:

MaPr h i 9 1 Ch-

Wpr OtziqiChanga

selected that was not the average, but was within 20% of d l three opinions. For example,

Percentaqes S;oz Agree bBecvcea Oizagrce Stromgty

Q D i t e 100 90 O0 70 6 0 5 0 40 3 0 20 10 t

100 90 60 70 6 0 50 40 10 20 10 1

100 90 0 0 m 6 0 50 40 JO 20 10 1

Figure 5.5 shows one of the parent state combinations of the Consirzxtion CZuims

100 90 1 0 10 6 0 50 40 3 0 20 10 1

100 90 00 ïU 6 0 50 40 JO 20 10 1

100 O0 8 0 7U 60 50 40 10 PO 10 1

100 90 8 0 70 6 0 5 0 &t) JO 20 10 1

100 90 00 70 60 5 0 40 3.0 2û 10 1

Mresul t in

I n I r c u i t i n

Wl rczultin

VUrczukia

Y i l l r d t i n

variable.

Belie/Nent.ork ..lnalysts o/Direcr Cos! RI& in Building Conîlrucrion 66

Wp 0-i h n q u

W p r DcignCbanqc+

Mapr 0c;iqm Chuiqa

M + c Otsigatbaaqc

Iilkpr Otsiqi Champ

The average of the expert opinions is 63.3%. As a result, the expert that returned 40% as

if1 #2 $3 Used

a response would be considered out of the acceptable range. A value of 60% was used in

6

the model to bring that response into the acceptable range. The 40% response is therefore

within the acceptable range, as are both other responses, and no expert was re-consulted

Figure 5.5: Example of situation where average value was not selected

Guod PM daims mitigation

Minor or no Field Clairns

Major . - . - Delag Claim. Maior Design Claims

about this question. A complete list of the survey, expert-based probabilities and the fmal

Maior Construction CIaims

probabilities are shown in Appendix 1. Figure 5.5 is a sarnple of what may be found in

the appendix.

5.4 MSBN MODEL

5.4.1 MODEL CONSTRUCTION

Microsofi Belief Network (MSBNTM) \vas the sofhvare used to constnict and evaluate the

completed belief network model. A systematic method for building the model on the

computer was followed. The steps were:

1. Enter the most dependent node on the model.

2. Enter the next most dependent node on the model.

3. If a relationship exists between the most recently entered node, and a

previously entered node, draw a directed arc fiom the less dependent node

to the more dependent node.

4. Retum to step 2, uniess no more nodes need to be entered.

These steps were followed to ensure that no circular paths were constructed.

Belief Nenrork .4naiysis of Direcr Cosr Risk in Building Consrrtrcrion 67

Once ail of the nodes and arcs were entered, appropriate variable states were assigned to

each variable. For variables that required asyrnrnetric assessment, the structure of the

asyrnrnetric assessment was inputted next.

Finally, the probabilities developed as a result of the efforts descrïbed in this chapter was

entered. It was, of course, important to ensure that no errors were made. For Predictor

Variables, the MSBNTM text file was used to input probabilities. The text file was used to

reduce the time involved in entering the probability data.

5.4.2 MSBN TEXT FILE

Much information can be gathered from the MSBN iext file. In addition to a graphical

interface, MSBN provides a text file format to facilitate development and review of the

model. Variable names, states, asyrnmetric asseçsment, and conditional probabilities are

al1 contained in this document. Figures 5.6, 5.7 and 5.8 are excerpts from the text file

that show node name and state definition, conditional probability data, and asymmetric

assessment structure.

The first section of the text file is shown in Figure 5.6. Included are the node title

(StblEqpmntAvlblty) , node name (Suitable Eqziipment AvoiZabili!y), type (type:

discrete[2] - variable with 2 discrete states), and states (" hadequate", " Adequate").

"Position" refers to the physical CO-ordinates of the node in the graphical interface.

Belief ~Venvork Analysrs olDir2cr Cost Ri& in Building Constnrctmn 68

node StblEqpmntAvlblty C

name: "Suitable Equipment Availability"; type: discreteE2J =

E "Inadequate", "Adequate"

1 ; position: (L4065, 14665) ;

Figure 5.6: Text file node definition - Srtifable Eqrtipmenf Avaiiabifity

The probability portion of the file shown in Figure 5.7 first lists the parent variables

(S tblEqpmntAvlblty 1 MtrlEqpmntLss, LclCnstrctnMrkt. Geography), then the

probabilities. The code used to denote wliich parent state combination applies to which

probability looks like:

p r o b a b i l i t y ( S t b l E q p m t A v f i c 1 t y I M t r l E a g m n t L s s , LclCnscrctnMrk:, Geography) {

(O, O, O) : 0-07, 0.93; (O, O, 1): 0.07, 0.93; (O, 0, 2): 0.07, 0.93; (O, 1, 0): 0.6, 0.4; (O, 1, L) : O -37, O. 6 3 ; (O, 1, 2): 0.2, 0.8; (O, 2, O): 0.4, 0.6; (O, 2, 1) : 0.55, 0.45; (O, 2, 2): 0-3, 0.7; (1, O, 0): 0.07, 0.43; (1, O, 1): 0.07, 0.93; (1, O, 2) : 0.07, 0.53; (L, 1, O): 0.7, 0.3; (1, 1, 1) : 0-55, 0.45; (1, 1, 2 ) : 0.2, 0-8; (1, 2, O): 0.75, 0.25; (1, 2, 1): 0.75, 0.25; (1, 2, 21 : 0.3, 0.7;

- -

Figure 5.7: Suifuide Equipment AvuiiubiIity ConditionaI Probabilities

With states nurnbered starting at zero, this code applies to the #1 state of #1 parent

variable, #O state of #2 parent variable, #2 state of #3 parent variable. The #O state of a

parent variable is the #1 state listed in the text file for that variable, the #1 state of a

Belie/Nenvork Analysis oJDirecr Cosr Risk rn Biniding Conswucrion 69

parent is the #2 state listed, and so on. The probability of the #O child state of the

variable StblEqtAv o c c h g is 0.07; the probability of the #1 child state is 0.93.

node StblEugmntAvlblty I

l eve l O p a r en t LclCnstrctni-4rktr Level L s t a t e O , l eve l 1 s t a t e 1, l eve l 2 pa r en t Geography, l eve l 3 s t a t e 2, l e v e l 3 s t a t e 1, l eve l 4 Garent MtrlEqpmntLss, i e v e l 5 s t a t e O, l eve l 5 state 1, l eve l 3 s ta te O , l eve l 4 paren t MtrlEqpmntLss, l eve l 5 s t a t e O , l eve l 5 s t a t e 1, l eve l 1 s t a t e 2, l e v e l 2 parent Geography, l eve l 3 s t a t e 2, l eve l 3 s t a t e 1, l eve l 4 pzren t MtrlEqpmntLss, l e v e l 5 s t a t e O , l eve l 5 s t a t e 1, l eve l 3 s t a t e 0, l e v e l 4 paren t MtrlEagmntLss, l eve l 5 s t a t e O, leveL 5 s t a t e 1

Figure 5.8: Asymmetric Assessment Structure - Srtitable Equipment Availability Text File

Figure 5.9 is the graphical representation of Fi,we 5.8. Each level of the graphical

format is represented in the text file by a line of text.

Be fief Nenvork Annlysis of Direct Cost Risk in Building Constnrct~on 70

terialIEquipment Loss

al/Equipment Loss

riaVEquipment Loss

Figure 5.9: Asymmetric Assessment Structure - Srrifnble Equi'pment AvailabiMy Graphical FiIe

5.4.3 USING THE MODEL

In order to use the model, the user need only instantiate the variables according to the

situation as it is known for a given construction project. Microsofi Belief NetworkTM

provides a separate evaluation tool for this purpose. Following instantiation of the

appropriate nodes on the network, the probabilities associated with the likelihood of each

state for each variable c m easily be read fiom a chart. Figure 5.10 shows part of an

exarnple evaluation of the rnodel.

The left side of the screen shows the variable name (first colurnn), the variable state

(second colurnn; if the variable is not instantiated, the statement "Not Observed" is found

there), and whether the variable is included in the spreadsheet on the right side of the

page-

Belie/Nenrork Analysis of Direcr Cosf Risk in Btrilding Consrnrcfion 72

lnadtquate Y u Inadetpaie Abwed Folbdden Moderate Extrant Other Na oba u Raitine Rok to contractas Risk m owner Risk shared CMtiactor Falf No artrador fait Lump- Unit ctice Guaan(eed M m

Figure 5.10: Sample MSBN Evaluatiou

The right side of the screen shows the variable name (first colurnn) and the likelihood of

each state occumng for each variable. By reading the Iikelihoods of each of the

Equipment Cost, Marerial Cost, and Labozrr Cosr variable States, one can predict the most

likely cost overrun for each direct cost category, and consequently predict the direct cost

overrun for the entire project.

BeliejiVenvork Analyses of Direct Cos[ Risk rn Building Consrnicrion 72

Chapter Six: Mode1 VerificationNalidation

6.1 INTRODUCTION

The completed belief network model is cdled CORAL-PRO (COst Risk AnaLysis using

PRObabilities). Following the development of the CORAL-PRO model, it was most

important to ensure that the rnodel was predicting results that were reasonable and

accurate. This involved two major steps. First, the sensitivity of the model to evidence at

various nodes was tested. This ensured that the mode1 was working in the expected

manner, and that it was not highiy sensitive to evidence at any given node. Following the

sensitivity analysis, the model was tested with information fkom completed projects. This

step was taken to ensure that the mode1 is producing accurate results.

6.2 SENSITMTY ANALYSKS

MSBNTM does not have an automated sensitivity analysis function. As a result, either

another software package must be used, or a program m u t be written to test the

sensitivity of the model. Neticam is another belief network software package that does

perform single variable sensitivity analysis. That is, it changes the state of each variable

in turn, and assesses the change in the probabilities at the predictor nodes. This allows

analysis of whether predictor variables are "moving" in the expected manner. It also

allows determination of the extent to which the predictor variable probabilities change

when evidence is entered.

Belief Nenvork rinalysis of Direcr Cosr Rtsk in Building Constnrcrion 73

Sensitivity analysis was performed for three reasons. First, it is important to determine if

the model is reacting in the manner expected; that is, when evidence is entered that

should increase the likelihood of a cost overrun, the likelihood of a cost overrun should

increase. Second, if the model is particulady sensitive to a given variable, the

probabiiities entered in the model can be checked for errors. If no errors exist, then the

degree of sensitivity must be reviewed to determine if it is reasonable. Finally, extreme

value testing involves setting each of the rnodel variables to, in the first case, their

negative state, and in the second case, their positive state. This ailows determination of

the range of possible values that the model may output.

Based on the sensitivity analysis, it was determined that the model was acting in the

manner expected. Each piece of evidence entered moved the predictor variables in the

direction expected. In addition, none of the predictor variables proved to be particulariy

sensitive to any of the other variables in the model.

Extreme value testing of the mode1 found that the minimum expected value of the

predictor variables is -12%. The minimum expected value is the lowest possible value

that the model may predict for cost ovenuns. The maximum expected value is 102%.

The maximum expected value is reasonable, according to expert interview. Experts also

felt that the minimum value was reasonable, although they did identify the possibility of

being lower than that value (Le. diere is a cliance of being more than 12% under the

budget). On the other hand, in the normal range of projects. expert interview determined

Beliej'h'envork Analysis of Direct Cost Risk in Biulrling Constnicrion 74

that the -12% to 102% range would encompass most of the projects completed,

especially given that this model is limited in scope to long term projects.

6.3 MODEL VALIDATION

Cost data for two projects were used in order to calibrate the model. Revay and

Associates, Ltd., a firm that works in the construction claims business, provided access to

their files to search out this information. Many files with cost data were found, but only

two contained the data required to calibrate this model. The information required is:

4 Budgeted Project Cost

+ Final Project Cost

+ Conditions of the project

By comparing the original project cost to the final project cost, one can determine the

degree of cost overrun on a given project. The only problem encountered in the

calibration of the model was that the budget data given in the files is given as a g r o s

project budget (Le. budget is not divided into materials, equiprnent and labour costs).

CORAL-PRO does differentiate between these categories, and as such, the proportion of

the project budget devoted to each category must be determined. Average values were

used instead to calibrate this modeI. Consuitation with project managers at Pearson

International Airport New Terminal Building construction revealed that, on average, the

amount that each budget category is worth is approximately as follows:

+ 10% of project budget devoted to equipment

+ 40% of project budget devoted to materiais

50% of project budget devoted to labour

Beliej3iVenvork Analysis of Direct Cosi Risk in Building Consrrtrciion 75

This data allows the model to be calibrated, on an average basis. The following is the

information regarding the two projects used to calibrate this model. Fictional narnes are

used in order to protect the confidentiality of the claim participants.

6.3.1 PROJECT ONE: ABC MANUFACTUR~NG FACILITY

XYZ Contracting hired to perforrn construction services on the ABC Manufacturing

Facility. Following construction they submitted a claim for additional compensation on

the bais that the contract was subjected to signifiant modification and rearrangement

during performance, and was ultimately performed under substantially different

conditions to those contemplated by the contract. It was found that the following

conditions existed on the project:

Excessive Overtime

Increased Man-hour Costs

Lower equipment and labour productivity

Excessive design modifications

Incomplete design, errors in design

Construction Delays

Poor site accesdegress

Suitable equipment unavailability

No budget revisions allowed

Increased volume of work compIeted

Be/ie/Senvork Rnalysis o/Direcr Cosr Risk in Birilding Construction 76

In addition to these conditions that were found to directly contribute to the cost overnui,

the following are project charactenstics that also corresponded to variables in the cost

model:

Urban Geography

0 Value Engineering not practiced

PM ineffective in clairns mitigation

Private fiuiding source

Each of these factors were entered as evidence into the cost model, and the predictor

variables were used to predict the cost ovemin with respect to the cost of labour, cost of

equipment and cost of materials. Table 6.1 shows the results.

As c m be seen, the cost of equiprnent is predicted to be 82.9 % greater than originally

budgeted, the cost of labour 67.2% greater, and the cost of materials 79.1% overnui. The

actuai total cost overrun for this project, was 78.4%. Given the average ratio of

equipment cost: Iabour cost: material cost is equal to 1:5:4, the predicted cost of this

project is 73.5%.

Table 6.1: Predicted likelihood of various cost overruns for each cost category, ABC Manufacturing Facility

Prediction of a cost o v e m to within 5% on long-term construction projects may be

considered quite good, and acceptable given that the goal of this mode1 is to provide

Belief Nenvork Anat'ysis of Direct Cost Risk in Building Constntcrion 77

Cost of Equipment Cost of Labour Cost of Materials

+I l%

32.1%

8.1%

19.7%

+55%

16.6 % 25.4 % 16.9 '%O

+3S%

6.2%

14.9 ?40 8.5%

+95%

28%

18.6 YO 26.6 %

+75%

25.9 YO 27.1 YO 24.7 ?40

+15%

1.2%

5.0%

3.0%

-25%

0%

0.1%

0.1%

-5%

0.1%

0.9%

0.6%

Expected Value +82.9%

+67.2%

+79.1%

project managers with a guideline. This mode1 is not intended to replace the intuition of

a project manager, it is meant to provide backup evidence. In this respect, a 4.9%

deviation is quite acceptable-

6.3.2 PROJECT TwO: 123 COMPANY BUILDING ENVELOPE RESTORATION

"Construct-CO" contractors were hired by 123 Company to restore the exterior envelope

of the 123 Company Building. Dwing Sie course of the work, Construct-CO submitted

that the originally planned scope of the work was radically altered by 123 Company

through the extreme variation of the quantities of work to be completed for various unit

price items, and by the introduction of substantial additionai scope to the project through

change orders. The following statements of fact about the project were made in the daim

report:

Significant scope increase

Extensive change orders

Major Construction delays

Budget revisions allowed

Inadequate site investigation

Increased volume of work cornpleted

Maj or overtime

Loss of equipment and labour productivity

Major labour congestion

Behef ~Vknvork Anaiysis of Direct Cosr Risk in Building Consrructron 78

In addition, the following conditions were characteristics of the project:

No value engineering

Urban geography

Poor PM claims mitigation

Low altitude

Public fünding source

Risk shared by contractor and owner

The model was used to predict the expected final cost overrun. Table 6.2 details the

results.

The actual cost overrun on this project was 62%. Given the proportion of overall costs

by category, the model predicts that the actual cost overrun on this project will be 70.5%.

This means that there is an 8.5% difference between actual and predicted costs. A

difference of 8.5% is slightly more than would be desirable, but reasonable given that the

model is meant only as a guide.

Belie/Nenvork Rnalysis of Direct Cost Risk in Building Cons~ntcrion 79

Table 6.2:Predicted Iikelihood of various cost overruns for each cost category, 123 Company Building

Cost of Equipment Cost of Labour

+9S%

12.5%

19.8%

+115%

5.6%

8.9%

~ z f / .8%15.22%1 23.7% 1 17.1% Materials

+75%

30.1%

27.5%

9.6%

+55%

24.3%

24.6%

4.1%

+35%

20.4%

13.9%

1.2%

+15%

11.5%

4.5%

0.3%

-5%

4.5%

0.8%

76.6%

- 25% 1.2%

0.1%

Expected Value 55.2%

68.7%

6.3.3 VALIDATION DISCUSSCON

Testing a complex model like this one by sampling two projects should not be considered

to be an exhaustive exarnination of the accuracy of this research- It does, however,

accomplish the goal of proving that, at Ieast in a couple of cases, this mode1 is reasonabry

accurate. Further testing with longer-term projects should be conducted to show more

decisively that the model works or where modifications should be made to improve it.

BelieliVenvork Anaipis of Direct Cosr Hisk in Building Consfruction 80

Cha~ter Seven: Conclusions & Recommendations

7.1 CONCL~SIONS

This research sought to develop a model that would serve to aid project managers in the

prediction of cost overrun in long-term construction. To that end, an extensive literature

search was conducted to identify any and dl risk variables to project construction cost.

To begin with, 75 nsk variables were identified. Expert input was solicited to determine

the relationships between any two risk variables on the list. This effort resulted in a

network model that showed ail risks to construction cost, and any relationships between

those risks.

Unfortunately, while almost complete, the CORAL-PRO mode1 was irnrnensely complex.

Some variables had greater than IO parents. Some variables would have required the

elicitation of thousands of probabilities. A significant amount of work subsequently

fo1Iowed to reduce the effort required fiorn voIunteer experts. This involved the

following processes:

Divorcing

Relationship Elimination

Asyrnmetric Assessrnent

Parent State Combination Ranking

Probability Curve Development

Each of these techniques reduced the number of relationships andor the nurnber of

probabilities required.

Belief Neniwrk .4naiysis of Direcf Cost Risk in Btrrlding Constniction 8 1

Following simplification of the model, conditional probabilities were gathered for each of

the cause-effect reIationships. In most cases, these probabilities were obtained using

expert survey. In some cases, however? normal probability curves were used (predictor

variables, and divorced variables). In other cases only some of the parent state

combinations were surveyed for a given child variable. The other state combination

probabilities were interpolated using standard regression techniques.

Finally, afier the mode1 construction and probability solicitation, the completed model

was subjected to a sensitivity analysis, and tested with data from actual completed

projects.

As a result of the extensive modeling research, a belief network mode1 was developed

that predicted results of actual tested projects to within ten percent.

It rnay be concluded that:

8 Long-term projects are subject to a tremendous amount of risk.

No construction project could be characterized as easy or routine since

every construction project is different and subject to different challenges.

in particular, long-term construction meets more challenges that shorter-

duration projects simply because time allows more opportunity for things

to go wrong. In all, 75 risk variables to construction cost were identified.

Subsequent risk variables were added for model manipulation, but the 75

initially-identified risk variables constitute a collection of uncertainties

that rnust be considered whenever undertaking a long-term construction

project.

Construction of belief networks requires a good deal of costhenefit analysis

As stated earlier, a tremendous effort was expended trying to reduce the

nurnber of probabilities required in subsequent stages of research. This

effort was not without a corresponding reduction in model completeness.

Testing of the model shows it is performing well, but may not accuratety

represent actual practice. This is an issue with al1 model development;

simpliQing assumptions usually result in a loss of tnie representation.

r Belief Networks provide an excellent means for understanding situations involving uncertainty

Belief Networks allow the mode1 builder to actually "see" the situation

being modeled. Directed arcs show relationships between mode1

variables. This model in particular allowed the mode1 builder to see which

factors most directly affected budget ovemns, and which were mitigated

by other factors. This allows the model user to concentrate more on those

variables that have greater impact. It aIso facilitated discussions with

experts because the graphical nature makes the model very intuitive to

understand.

BeliejiVenvork Analysis o/Direcr Cosr Risk in Building Consrmction 83

This mode1 specificaïIy predicted cost overruns on two completed projects to within 10%

The completed model came within 10% of the actual value of budget

o v e r m on the corresponding project. This is encouraging if not

conclusive. The belief network mode1 certainly needs to be tested firrther,

but initial resuits show that it is working.

7.2 CONTRIBUTIONS

There were several goals and objectives identified in the introduction. This section seeks

to identie whether these goals have been achieved. As a surnmary, the objectives and

milestones identified were:

development of a belief network to predict cost overruns,

identification of factors affecting the cost of construction projects,

determination of the marner in which these factors affect cost,

determination of the degree to which these variables affect cost.

initial testing of a more effkient expert surveying method,

The study of risk as it pertains to construction cost has been furthered significantly by

this research. The following is a hst of contributions to the field.

1. A mode1 to predict cost overmn on long-term construction projects was

developed. This model was found to work quite well on two completed

construction projects.

2. 75 risk variables to cost in total were identified, ranked and classified. No

such Iist was found by the author prior to the construction of this model.

Befief Nenvork Anabsis of Direct Cosr R~sk in Bdding Consfnrctron 84

3. A network was constnicted that model cause-effect relationships between

each of the risk variables identified in this research.

4. Quantification of each relationship in t a s of probabilities for parent state

combinations was achieved.

5. A technique to reduce expert effort was developed. This technique

involved ranking of parent state combinations, selective surveying of some

of the parent state cornbinations, and interpolation of intermediate values.

This method of surveying certainly needs more attention on future

projects.

As c m be plainly seen, contributions 2, 3, and 4 are realiy "sub-contributions" of number

1. As stated in the introduction, however, these interrnediate milestones are of academic

significance, and are important contributions to the art and science of construction

engineering and management.

7.3 RECOMMENDATIONS

The most important M e r research that needs to occur is an examination of the

effectiveness of this model on many other long-terni construction projects. The

calibration effort undertaken as part of this research was effective and encouraging, but

certainly not exhaustive. Data from more projects need to be sought out and used to test

the cost model. These projects need to be more long-term in nature than the two projects

tested. Only then can the model be conclusively proven to be effective and reliable.

BelieJiVework Anaipis of Direct Cos[ Risk in Building Cons~ntcf ion 85

Further development of this model can occur during the continuous testing process. As

more projects are added to the database of tested works, probabilities within the model

can be refined and updated. Given the changing nature of the construction industry, it

would be prudent to continue the updating of this model.

Finally, the new method for surveying experts involving interpolation of results needs to

be M e r studied and refined. If anything was learned fiom this research, it is that

individuals working in the construction industry are incredibly busy. Those contributing

to this work were very accornmodating and helpful. but that accommodation needs to be

retumed. To that end, any effort made to reduce the arnount of time required on their part

should be made. Further study of the interpolation survey method needs to occur. If

work is dom to improve the interview process, research using the methods descnbed in

this report can occur more efficiently, and the art and science o f risk management can

progress even M e r .

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Construction Industry Institute, 2990. The Impact of Changes on Construction Cost and

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Cooper, D.F. and Chapman, C.B., 1987. Risk Analvsis for Large Proiects: Models.

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Design News, 1997. "Value Engineering: The Right Material, in the Right Place, at the

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Belie/lVenvork Analysis of Direct Cost Risk in Building Consznrcfion 87

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Dozzi, P., Hartman, F., Tidsbury, N., Ashafi, R., "More Stable Owner-Contractor

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Henrion, My Breese, J.S., Horvitz, E.J., 199 1. "Decision Analysis and Expert Systerns."

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Henrion, M., 1989. "Some Practical Issues in Constructing Belief Networks."

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Belief Xenvork Anaiysis oj' Direct Cos1 Risk in Building Construction 88

Hinze, J., Pederson, C., Fredley, J., 1998. "Edenti&ing Root Causes of Construction

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Jensen, F., 1996. An introduction to Bavesian Networks. University College London

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Belief.Venvork Anafysis o/Direcr Cosr Risk in Brrrlding Consrnicfion 91

Appendix A: Risk Variable Information

Belie/iVenvork Analysis of Direct Cost Risk in Building Constnictton 92

Risk NamelSource 1 Risk Definition Equipment Cost 1 Total cost of equipment used (To oe applied ro on the projecr. Includcs each of rhe projecr purchse or rental cos& fuel cosr centres) cost, repais. etc.

O be applied ro the consmction of the project each o f the proiecr COSI centres

Risk States -25%

1 Matenal Cost (To 6e applied ro each of ihe prcjecr cost centres)

(crr 19891

I alterations in project content or schedule.

Construction claims (CI1 19891

Risk Parents Availability of suitable cquiprnent;

TotaI cost of materials for project use.

Claims by project participants for more t h e or money due to

Construction market escalation: Equipment Productivity General Inflation Value Engjneering Construction Claims

+ I l s % -25% -5% +l5?6 i-3 5% +55% +75% +95%

Qualified local labour Labour Productivity: Overtime; General Inflation; Project G e o ~ n p h y Construction delays;

Construction market price escalation; Design changes; Material waste; Scope creep; Material Shortage Value Engineering

i l 15% Major constniction claims: Modemte construction daims; Minor or no construction

P M claims mitigation 4 For Divorcind

PM claims mitigation: Field claims: Delay cfaims: Design clairns;

Design daims (For Divorcino)

Field claims (For Divorcino)

Delay claims 1 For Divorcing)

clairns node) The PM'S experience and skiII in diffusing construction claims before they becorne a problern. (Used in divorcing for Construction clairns node)

Construction clairns that are related to design factors. (Used in divorcing for Construction claims node) Consuuction claims that are related to field factors. (Used in divorcing for Construction claims node) Construction claims that are related to delay factors. (Used in divorcing for Construction

1 tor in the original budger II Cost Acrountine 1 The prompmess and reliabilitv

clairns Major Design related claims: Minor or no Design related claims

Major Field relatcd claims: mino or or no Field related claims

Major Delay related claims; mino or or no delay relatrd cfaims

Overtime fcrr 19891

- I of the cos; reporting and -

accounring syslern. Assume

Design changes; Scope Creep: Design Subrnittal:

Trade coordination: Ground Conditions; Defective Work

Construction Delays: Overtime Long Work Stoppages

Work above the espected amount that is not accounted

1 that the accounting is accurate. Value Engineering 1 A tool used to eliminate -

(Expert) redundancy in design and construction. The goal is [O

reduce project cost

Project manager effective at reducing construction cfaims that occur. Project manager not effective at rcducing construction

Qualified key PM personnet: PM

daims that occur 1 more ovenime than expected; 1 Construction Delays; As much or las overtime 1 Labour Productivits:

Untirnely I than espected Timely;

Scopr Creep PM

Value Engineering Practiced; Value Engineering not

Budget revisions: PM;

~racticed-

Beiief ~Venvork Anaipis of Direct Cost Risk in Building Consrrucrion 93

Constmction Deiays

Construction Delays (CI1 1989)

Major construction delays; mino or or no construction delays;

Time Iost with respect to the schedule.

Labour delays; Logistics delays; Design delays; Environmental delays; Failure delays

H Risk Name/Source 1 Risk Definition FaiIure delays 1 DeIays in construction due to Flanazan. man

I 1 Subcontractor going out of

the g&ng out o f business of one of the project participants.

Contractor Failure Flanaean. Norman

Failure Flanaoan. Norman 1

Contractor going out of business

- - - -

1) =lier Failun 1 Supplier going out of business.

Il {For ~ i v o r c i n 9 I Labour issues. (Ùsed in divorcing Construction delays

(Flanaew. Norman I993) Labour delays Construction delays related to

1 node) II Design delays 1 Construction delays related to

Logistics delays {For Divorcino)

II ( ~ o r ~ i v o r c b g ) I Design issues. (Üsed in divorcing Construction delays

node) Conswction delays related to logistics issues. (Used in divorcing Construction detays

II 1 node) Environmental 1 Constmction delays related to

l Environmental issues. (Used 11 $%ivorcino) in divorcing Construction 1 delays node) 1) Land d e l a i 1 Construction delays related to

(For ~ ivor&o)

For Divorcing in a loss of labour productivity. (Used in divorcing labour productivity node)

the ground. (Used in divorcing Environmental delays node)

1

Labour productivity (Wideman 1992)

The amount of work done by labour per unit time.

Labour congestion [For Divorcino)

(For Divorcino)

Impedirnents to eficient completion of labour work. (Used in divorcing Labour

l personnel. (Used in divorcing labour productivity node)

Deviations that was expected to be done. CI1 1989

Labour design understanding

Risk States ( Risk Parents Major delays due ta failure; 1 Contractor Failure;

Understanding of design documents by labour

ino or dela& o r no delays due to failurer

Subcontractor Failure; Supplier Failure

Contractor fails: No contractor fails

Parent Only

Subcontractor fails: No subcontractor fails

Major Delays; Minor or no delaysr

Parcnt Only

Supplier fails; No supplier fails

Labour productivity: Defective work; Long Work stoppages:

Parent OnIy

1 Trade coordination blajor delays; ) Materials Delive-; Minor or no delays 1 Conswction/Ops interference

Major delays; Minor or no delays

Design changes; Design SubmittaI

Major delays: Minor or no detays

Major delays: Minor or no delays

Ground conditions; Geology; Land related natural disaster

Land deIays; Environmental scnsitivit).: Weather extremes

( Labour design understanding Occur frequently: 1 Material Shonage;

Less productive as expected; & productive or more productive than espcctrd

Occur infrequently

Short breaks; Labour congestion; Defective Work;

Suitabk equipm>nt availability: Labour injuries/ accidents: Climate

Labour advenely affected by vehicle and person congestion; Labour not adversely affrctrd by vehicle and penon congestion

requirements; Design changes Qualified Local Labour,

Number of workers on site; Trafic congestion; Constniction/Ops Interference

Poor understanding; Good Understanding

More work encountered during construction (ive. dewaterinp, etc.); As much work or les than expected

Design Quaiity; Construction rechnology

Design Qua1 ity; Tenant Requirement Change: Ground Conditions; Design Changes; Defective Work

Befie/:Venvark Annfysis of Direct Cosr Risk in Btrrlding Constnrctron 94

Matenal Waste 1- Design changes 7 Defective work (CI1 1989)

Trade Coordination JWideman 1992)

I

Penal tics

market prices Wideman 1992

Il Foreign purchareci /

materials (CI1 1989)

Equipment producthity JWideman 1992)

Suitablc equipment availability (CI1 1989)

Risk Definition Inadequate materials on site for completion of the job

Material that is purchased for project use but is not used.

Changes in the design during the course of construction.

Construction deviations from design.

Cooperation and coordination of the various consvuction trades.

Violation of laws and niles of various regulatory bodies (OHSA, EPA etc.). Strikes. protest. public inquiries b a t atfect the timely completion of work.

The uncertainty regarding timeiy delivery ofproject materials to the site. Especially when JIT drlivery is used. The use of strategies like partnering to ensure a cooperative project effort

Increases in project costs that are anributable solely to the fact that some project aspects are international in nature.

The use of materials o r equiprnent tiiat originate outside of the project's country.

Materials required to build the project that are close enough to the site that they can be obtained in a timely rnanner.

The amount of work that equipment does per unit time.

Equipment that is capable of doing the work required and is available at a reasonable cost to work on the projecr

Risk States Risk Parents Frequently inadequate Design Changes: malerials on site: Material/Equipment Loss: infrequentiy inadequate Materials D e ~ i v e r ~ materials on site Material Waste Major material waste; Defective Work Minor or no material waste:

Major design changes; Design Quality; Minor or no design changes; Scopc Creep:

Design Team coordination: Complexity/ Constructability of

1 Design: maio or mistakes: 1 QualifÏed local labour: ino or mistakes or no I rade coordination: mistakes Design Quaiity;

1 CompIexity/ ConstructabiIity of Design

Good communication and Qualitïed key PM personnel; coordination; Complexity/ Constructability of Poor communication and design; coordination Physical Project Size Major penalties applied; Environmental Sensitivity Minor or no penalties applied; Major construction Parent Onlv stoppages; Minor or no construction

Frequently late

Partnering practiced: PM; Partnering not practiced Qualified kry PM Personnel

As expected or lower Foreign Purchased Goods

Materials andlor equiprnent Exchange Rates; purchased internationally: Suitable Equipment Availability Marerials and/or equipment purchased domestically

Adequate quality materials Local construction market available; insuficient quality materials availabIe

Equipment less productive Suitable Equipment Availability; than expected: Ground Conditions; ~ ~ u i ~ m e n t as prodiictive or Altitude more productive han expected

available: Local construction market; Insufikient equipment blaterial/Equipment Loss available

Belief rVenvork Jnaiysis oJ- Direct Cost Risk in Building Constnrction 95

CI1 1990

accidents CI1 1989

labour CI1 1989

FIanaoan, Norman - 1993)

Survey

CI1 1990

Design Quality 117

Budget revisions IF Requirement Change (Esuert)

Contract Clauses I r

Contractor payment type (CI1 19891

PiCf work familiarity CI1 1989

due to the& ;andalism or in or or no losses occur. damage. Physical injriry to labourers. Major injuries occur.

Minor or no injuries occur:

Labour workers who are able Adequate qualified labour to perfom the required wvork personnel available; and are avaiiable to work on Insuficient qualified labour this projec~ ( personnel available Geologicnl conditions that are ) Ground conditions torse

when designs are made. Ground conditions as

Availability of design Design on tirne; documents when required by Design late construction. Quality of completed design High quality design; documents available to 1 Low guality design ( e m n construction workers during f present. omissions, etc.) the course of the oroiecl. 1 Changes in the project design that alter the work that need be done.

Scope cretp present: Scope creep absent

The owner's willingness to I Revisions allowed; alter the budget afier the Revisions forbidden

I change during consinicrion; No tenant requirement

pro-iect has bëgun. Changes in final design preferences by tenants afier commencement of the project

Major tenant requirement change during construction: Minor tenant requirement

of the job on time. on budget. 1 - -

No relief for force-maieure f Risk transferred to

The project manager's commitment to the complet ion

clauses, Diffcring site conditions, Not responsible for quantity variations, HoId Harmless, No damage for deIay, Contract-imposed procurernent iimitations, Warran ties and guaranties, Bonuses and shared savings. Retention. Convacr penalties (liquidated damages. etc.) Lump surn, unit price. guaranteed mauimurn. cost reimbursable.

change during construction Project manager proactive; Project manager reactive

con tract ors; Risk transferred to owner; Risk shared by contractors and owner

Lump sum; Unit price; Guaranteed maximum;

1 Cost reimbursable The project manager's 1 PM farniliar and experienced experie6ce with simi tar projects.

PM'S understanding of the site environrnent (location, geology. population, government, etc.)

with type of constnktion; PM unfamiliar and inexperienced with type of COflStNCtlOIl

Parent Onlv

Local construction market:

Geology: ArchaeoIojica[ survey

Parent Onlv

Design Team Coordination: Scope Creep

Project manager familiar with area; Project manager unfamiliar with area

Risk Narne/Source Risk Definition ( RiskStates Materiai/equipment Loss of equipment or materials 1 Maior losses occur,

m.

-

-.

-

Construction Technology Requirements; Design Team Coordination;

Risk Parents Site Security

-

-

-

- -

-

SCO& Creep Tenant Requirement Change; Design team coordination

-

-

-

-

-

Owner Financial Stability

Parent Onlv

Qualified Key PM Personnel; PM work familiarity

Contractor Payment Type

Parent Onlv

Construction ~ e c h n o l o ~ ~ Requirernents

Qualified key PM personnel

BeliejNenvork Analysis oJ Direct Cost R~sk in Bztilding Consrnrcr~on 96

construction and existing site opentions-

The need for security and the ease at which the site c m be secured.

Vehicular trafic on and around the project site that impedes movement of construction vehicles. Available points of e n q and exit to project site.

The number of G d strïctness of perrnits required to do work.

Number of labourers, project management personnel. inspecton. etc. on site.

Environmental sensitivity of the surrounding environment

Need for unproven technology in constmction and operation of this project

Degret of difficulty of construction of this project.

Communication and cooperation benveen designers of different project componenrs.

People who are experienced in management of similar projects and are available to work on this project.

Shelter, food and other nccessities for construction staff- emergency services, communications, etc. The source of funds for the project - private or public sector.

Typical security arrangements; Atypicid security arrangementsl Movrment around site very impeded by vehicles: Movement around site largely

construccion and opentions; Little or no intertèrence

unimpeded Adequate accesdegress to

Competing Activity on Site: Trafic congestion

site; oress to Insuficient access/e=

site lnsufficient - unreasonable delays encountered when rrying to get on to o r off of site Cornplex permitting requirernents: Normal permitting requirernents Person-congrsted site: Non-person congested site

Parent OnIy

Site access; Number o f workers on site; Competing Activity on site; Physical project size Parent onlv

Parent onlv

sensitive; Environment not very sensitive

Environment very sensitive; Environment modentely

Parent Onlv

1

New technology required for 1 Complesity/ Constmctability of

Risk Name/Source Construction/ Operations Interference fE..upenl Site security fC11 1989)

T r a f i c congestion (CI1 1989)

Site access lcrr I 9891

Permits Required (Wideman - 19921

Number of morkers on site lcrr 1989)

Environmen ta[ sensitivity (CI1 1989)

Construction technology requirements (Cr1 1989)

CompIexity/ Constructability of design [CI1 1990) Design team coordination (ExD~~L)

Qualified key P M personnel [CI1 1989)

Construction Support Facilities (Cil 1989)

Funding Source {Widernan - 1992)

constmction; Proven technolog>- required

Design

Risk Definition The interference benveen

Complicated project; Routine project

Risk States 1 Risk Parents Major interference benveen ) Qualified key PM personnel;

-

Parent Onlv

-

-

-

-

-

-

-

-

-

-

4 -

management personnel available; Not rnough qualified project management personnel available

Good communication and coordination; Poor communication and coordination

Qualified key PM personnel

availablc: 1 Privately-funded job ( Government spending on

Adequate suitable facilities availablr: Not enough suitable facilities

Publicly-funded job 1 consuuction: Combination (private/public) Govemment

General area affiuence/wealth; Local construction market

Beliejh'envork Anaiysis of Direcf Cosr Risk in Bziiiding Consrnrcrion 97

Risk NamdSource 1 Risk Definition 1 Risk States 1 Risk Parents Construction 1 Fluctuation in pnces of 1 Higher than expected; Genenl Inflation; market escaiation (Exuert)

1 ) few resources tied up Owner financial 1 Fiscal situation of project 1 FinanciaiIy stable owner,

Local construction market (Eu~ert)

. -

stability 1 owner. 1 ina an ci al& unstable owner

consuuction iiarea in which project is being built

i\sexpected or-1ower than expected

Other construction projects that dmv on the same labour, equipment and resources as the given project

Govemment spending on construction: Local construction market

Area construction-satunted: Some othcr construction; Area construction-poor Construction saturated - most other labour, equipment and resources tied up. Construction poor - v e q

lcrr 1989) Physical project sixe JCII 1989)

Parent Onlv

Parent Onlv

Physical size of area on which the project is being built.

Parent Only Large project area; Srnall project area Large: dificult to shnre equipment, long travel from one point on site to others,

Competing activity on site (Cr1 1989) Availability of eneqg {Wideman 1992)

E~istence of other activities on the project site or adjacent to

Utilities <Cl1 19891

--

1 . - 1 construction is located. 1

Inflation 1 A mrasure of general price 1 Higher than espected: 1 Government Spending on

project site. Presence of required enera (elecuicity, fueI, gas, etc.) to the project site.

Area ailluence (CI1 1989)

(Ex~en] ( increases. - 1 ~ s e s ~ e c t e d or-lower than ( Construction

etc. Othrr activity competings No other activity competing

Layout of existing utilities on and around project site

Parent Onlv

Adequate energy readity available: Adequate energy not readily

Prosperity of people and industries in area in which the

Project Geography

available Utilities present, location known: Utilities present location unknown:

Government spending on construction

I I Exchange Rates ( Relative value of local 1 Worse than expected:

Parent Onlv

Utilities nat present Prosperous area; Non-prosperous area

{Stioliu and Boadwav 1994) Tax Rates (Widernan 1992)

lcrr 1989) I currency as compared to I As expecred or better than foreign currency. expected

Parent Onlv

Amount of rnoney that appIicable govemments are investino in construction.

Government espected Higher than usual: As usual or lowrr than usual

-

Money that must be paid to government as a percentage of revenue made.

Government Hi$er than espected: As expected or Iower than espected

Parent Onlv

Government (CI1 1989)

Land - related natural disaster

Belief Nenvork Analysis of Direct Cost Risk in Building Constnrcfron 98

Turnover of governrnent and the degree ofunderstanding in government of construction-

Weather Extremes f a 1 1 989)

A disaster of geology (e.g. carthquakr, landslidtt. etc.).

Stable government: UnstabIe govcmrnent

Unusually serious weather that affects the project

Parent Onlv

Disasters likely: Disasters unlikeIy

Geology

Extreme weather Iikely: E~treme wearlier unlikely

Parent Onlv

11 1 project site. 1 Extreme - not easy to adapt 1

Risk NamefSource Clirnate ICI1 19891

Geograp hy fc!i 1 989)

Risk Parents Parent Onlv

Risk Definition The nonna[ weather that c m be expected to exist on the

I

Belief Nenvork Analysis of Direct Cos( Risk in Builciing Constnrction 99

Risk States Modenre - easity adaptable to:

The proximity o f the project site to other civilization.

Gcology [cl1 1989)

* Altitude CI1 19891

tO Urban; Rural: Rernotr

level.

The composition and condition o f rock forniations underlçing

Parent OnIv

The vertical elevation of the project site as compared to sea

Low altitude (c3000tt above sea level) Favourable to construction: Unfavounble to constmction

. . -. . . - . - High altitude p3000ft above sea level)

Parent Onlv

Parent Onlv

Appendix B : Risk Relationship Survey

Belief :Vencork Anaiysrs of Direct Cost Risk in B!iilding Cons~rïcrion 1 O0

I l I l I I

tor, Nb, nippbr) Fribur.nLittddtlry, I l I I I I

BeliejNenvork Anabsis of Direct Cosf Risk in Building Constnrction 102

O t h u n v p r e o m t m c t i D n ~ i n i n r OabiirfinuiàrlstabüÏiy p w p r r * c c t , &

b m p t ~ ~ a a r i t r A v z i l r b i f i t r o f ~ Prtu-drrtilitia G.damar f fhaE .k&h GrnnlDtktioa ~ 0 f ~ V u n n m J l ! ~ o p c o ~ n

T u ma frdvne & t a

StabiiiîylrophirtPclMn o f @--nt

L u d & t e d ~ t u n i d i r u t u O r a d r L i k e e . etc1

S h Topocmphy Poteutid for Wt&r Ex- unutclinrit G.oqrphy (mbrn ptca. ZTmI, mzmte) Altir& hba

b a r d Qmirrr (nrk to contractor. 1bn4 -rh- mk) Coatractor Payment Type &=p. iait. gunnlerd m. etc.)

BelÏe/Nenvork Analysis of Direct Cost Risk in Building Construcrion 1 03

BelieJiVenvork Analysis of Direcl Cosr Risk in Building Consrnrcrion 1 O4

BeIiefiVenvork Anal),sis of Direct Cosr Risk in Building Consrnrcfion 1 05

Appendix C: Risk Survey Analysis

Belief Nenvork Rnaiysis of Direct Cos! Aisk in Bdi ing Construcfion 1 06

Cast Ouerrun

Partiçipant [contractor. sub. supplier) Failure-related delays

Contractor Failure

Relationships

Subcontractor Failure

Score Councs

0 1 1 ( 2 1 3

Subcontractor Fiilure

Suppiier Faiiure

Supplier Failure

Supplier Failure

Construction claims

Construction claims

l

Cost overrun

Participant failure related delays

Part ie i~rnt failure relatcd delaus 1 1 2

Contractor Faiiure

Partiapant failure related delays

Contractor Failure


Cost overrun

Contractar failure

Construction claims

Construction claims

Cosc o f equipment

Cost o f Labour

Project Manager Budget Correcting Measures

Project Manager Budget Correcting Meanires

Tirneliness o f Cost ReportingtAccounting

Timeiïness of Cost ReportingtAccounting

Construction Delays [not participant-failure relate4

Construction Oelays [not participant-faiiure relate4

Construction Oelays [not participant-failure related)

Canstruction Delags (nat participant-failure relate4

1 2 5 1

1 0 3 5

3

2 2 3 2

0 4 3 2

2 4 2 1

1 3 3 2

0 1 3 5

2 4 1 2

Unbudgeted ouertime

Unbudgeted overtime

Unbudaeted overtime

Construction Oelays [noc parricipant-failure reiated)

3 -

-


Supplier Failure

Casc overrun

Cost ovrrrun

Construction Delays [not participant-failure relateq

- -

2 4 1 2

2 6 0 1

2 2 3 2

2 2 3 2 - -

Construction claims

Cost OF equiprnent

Cost o f labour

Labour productiuity

Lahaur ocoductiuitu

Labour productiuity

Labour productiuity

Cnsr af materials

-

0 0 4 5

6 0 2 1

1 0 1 7 I ! Cost owerrun

1 Unbudgeted oueriime

Construction clairns

Proiect manager budget correcting measures

Cost overrun

Construction daims

Cost o f equipment

COSC o f labour

-

3 4 1 1

5 2 1 1

4 4 1 0

3 1 3 2

0 1 3 5

1 0 5 3

4 0 3 2

0 1 5 3 -

Unbudgeted ouertirne

Proiecc manager budget correcting measures

Cost of equiprnent

Cost of labour

Unbudgeted overtime

Construction delays (not participant M u r e relared)

Cost owrrun -

Cost of materials

Material Waste

Defectiue work -rnistakes

0 2 2 5

1 2 4 2

3 2 3 1

0 1 2 6

a 2 2 5

0 1 6 2

1 3 2 3

Oefective work - rnistakes

Oelective work - mistakes

Oefectiue work - mistakes

Oefectiue work -rnistakes

Coordination of Trades

-

Design changes

Design changes

Desian chanaes

-

Project manager budget correcting rneasures

Cost of materials

Construction claims




Oesian chanaes

Construction delays [net participant failure related]

Labour productivity

Cost o f materials

Materiai Vaste

Construction Claims -

Construction delays [not participant failure related]

Material Vaste

Defective work - mistakes

Canstruction clairns -

Cost of equipmenr

Constructian delays (not participant failure relate4

Labour oroductivitu 1 0

i?ehefrVefwork =Ina/ysis of Direct Cos[ Risk in B~ulding Consrrucrion 107

-- - -

0 2 6 1

0 3 5 1

2 3 3 1

Design changes

Design changes

.-

2 2 3 2

1 3 1 4

0 2 5 2

0 1 4 4

1 1 4 3 -

0 2 2 5

3 5 0 1

0 4 1 4

0 1 1 7 -

3

-p

-

Cost of materials

Defectfve work - rnistakes

--

3 2 1 3

0 1 2 6

2

2 1 2 4

3 1 2 3

4

Belief Xenvork Analysis of Direcr Cosr Hisk in Btirldrng Consrntcrion 1 O8

5

3

Bonding of ContractorslSubcontractors

Bonding OF ContractorslSubcontractors

Banding of ContractorslSubcontractors

eonding of Contractors~Subcontractors

Deviatian from enpected quantities of work

Oeviation from expected quantitiesof work

Oeviation from erpected quantities of work

Reguhtory Penalties

Regulatotg Penalties

Regulatoq Penalties

York Stoppages oabour strifelpublic opposition. unrest]

Vork Stoppages (labour strifefpublic opposition. unrest]

Work Stoppages [labour strifefpubfic opposition, unrest]

Materials delivery t o site uncertainty

Matenalsdelivery CO siteuncertainty

Presence o f a cooperarivelpartnering environment

Presence of a aooperativelpartnering environment

Presencc of a cooperativefpartnering environment

Presmce of a cooperatiurfpartneiing environment

Presence of a cooperativefpartnering environment

Presence o f a cooperaiivelpartnering environment

International market-related price increases

international market-related price increases



Use of Foreign purchased rnaterialsfequipment

Adequate quantity of quality materials in area

Adequare quaniiiy o f quality materials in area

Adequate quantity o f quality materials in area

Equipmcnt productivity

Equipment productivity

Equipment productiuity

Availabiiity of suitable equipment

Auailablty o f suitable equipment

Availability of suitable equipment

Material lEquipment Loss

Material IEquiprnent Loss

Material IEquÏpment Loss

Material IEquipment Loss

Labour lniurieslaccidents

Labour Iniuriestaccidents

Labour lniuriestaccidents


Labour In~urieslaccidents

Labour Iniurieslaccidents

Availability of qualified keg labour personnel

Availability of qualifitd key labour personnel

Availabiliiy OF qualiiied key labour personnel

Availability of qualified key labour personnel

Avaifability o f qualified key labour personnel

Bonding of ContractorslSubcontractors

Cost overrun

Proiecc manager budget correcting meanires

Design changes


Construction delays [not participant failure relate4

Labour productivity

Construction claims

Construction delays[not participant FaÏiure related]

Cost overrun

Construction claims

Proiect manager budget correctrng measures



Materials delivery to site uncertainty

Cost overrun

Cost of equipment

Proiect manager budget correcting measwes

Cost of materials - International market-related price increases

Cost of rnaterials


Use o f Foreign purchased materials~equipment

Cost of equipment

Construction delays (not participant failure relateq

Labour productivitg

Cost of equipment

Use o f foreign purchased materialsfequipment

Equipmenc productivity

Cost of equipment

Construction delays (not participant failure relate4 -

Cost o f mdtetiak

Avaiiability of suitable equipment

Cost of labour

Construction delays [no& participant failure related]

Labour productiviiy

Oefective work - mistakes

Regulatory penalties

Work stoppages

Cost of labour

Construction delays [nat patticipant failure relaied] p .

Labour productivity

Oefective work -mistakes

Labour lniuriesfaccidents

Contractor Failure --

Subconrractor Failure

Construction claims

Labour productivity


Construc<ion claims

Consauction delays [not participant failure relate4

Cost of materials

3 5 1 0

5 2 1 1

5 1 2 1

0 1 2 6

0 2 2 5

0 4 1 4

2 2 5 0

1 3 4 1

3 4 2 0

4 2 3 0

4 3 1 0

2 3 4 0

2 3 3 1

6 2 1 0

2 4 2 1

3 5 1 0

2 5 2 0

1 5 1 2

1 2 2 4

0 5 1 3

0 4 2 3

3 2 2 2

1 3 3 2

2 2 4 1

3 2 3 1

0 2 3 4

1 1 6 1

0 0 3 6

3 3 2 1

1 3 3 2

1 3 3 2

4 1 2 2

1 6 1 1

1 4 3 1

4

4

--

O

0

3 1 1 3

6 3 0 0

8 1 0 0

5 2 2 0

1 1 5 2

1 1 6 1

2 4 3 0

-

3 3 2 1

7 2 0 0

4 1 3 1

3 4 1 1

O

0 1 8 0

0 3 4 2

2

2 2 5 0

3 1 1 3

Proiect manageras abilitylwiilingness to meet obligarions 1 Timeliness of cost reporiingtaccounting 1 2 1 0 1 3 ) 3

Oeuiation from expecred quantities o f work

Unseen Ground Conditions




Unsecn Ground Conditions


Unseen Gtound Conditions


Timehess o f design

Belief Nenvork itnaiysis of D i rec t Cos! Risk ln Building Constnrctron 1 O9

Avaïiability of qualified key labour personnel

Construction daims

Cast of equipment

Construction delays (not participant failure relate4

Labour productivitg

Cost of materials

Equipment productkity

Availabiiity of suitable equipment

Deviatian from ewpected quantities of work

Construction claims

4 2 2 0

0 0 2 7

1 2 5 1

0 1 1 7

0 4 3 1

5 2 1 0

1 2 4 2

3 4 0 1

0 0 4 4

0 1 3 5 ---- Tirnefiness of design

Quality of design

Quality of design

Quafity OF design

Quality of design

Quality o f design

Quality of design

Completeness o f design

Cornpletenes of design

Completeness OF design

Completeness o f design

Completcness o f design

Cornpleteness o f design

Cornpleteness o f design

Scope Creep

Scope Creep

6

2

0 5 3 1

---- 0 1 6 1

6 0 1 1

0 1 5 3

2 4 3 0

Scope Creep Unbudgeted overtime

Construction delays [noc participant failure relate4

Labour productivity

Oefective work - mistakes

Design changes

Deviation frorn erpected quantiries of work

Unseen ground conditions

Timeliness o f design


Labour productivity

Design changes

Scope Creep

Scope Creep

Scape Creep

Scope Creep

Scope Creep

Scope Creep

Scope Creep

Scope Creep




Change in Tenant Requirernents

Change in Tenant Requkements

Change in Tenant Requirements


Change in Tenant Requïrements


Change in Tenant Requirernents

Change in Tenant Requircrnents

Proiect managrrSs abilityfwillingness to met t obligations

Project manager's abilitylwillingness to meet obligations

Proiect manager's abilitylwiilingness CO mecc obligations

Proiect managerw+ abilityiwîilingness to rneet obligations

0 0 4 4

0 3 2 2

0 0 2 6

0 2 5 1

1

2 1 1 4

0 0 3 5

0 3 1 5

0 0 2 6

1 2 3 3

--

O

5

1 2

O

Oeuiation from expected quantities of work


Timeliness of design

Quality of design

Construction claims

Cost of equipment

Cost of materials

Design changes

Adequate quantity OF quarity materialsin area

Availabiiity OF suitable equipment


Timeliness of design

Qualicy of design

Cornpleteness of design

Cost overrun


Deviation from ewpected quancities of work

Construction Claims

Cost of materials

Material Waste

Design changes

Avaiiahility of qualified key labour personnel

Deviation [rom erpected quantities of work

Completeness of design

Scope creep

Cost overrun


Unbudgeted overtime


O 3

0 4 2 3

0 1 1 7

0 2 5 2

O 1 7 1

0 1 6 2

1 3 3 2

1 0 3 5

4 3 1 0

3 3 2 0

4 3 0 1

0 2 2 5

0 2 6 1

0 5 2 2

1 1 5 2

0 2 5 2

1 2 5 1

0 1 4 4

3 3 2 1

1 4 4 0

0 1 1 6

3 4 0 2

3

1 4 4 0

3

Proieet manager's abilityfwiningness to mcet obligations Construction delays [not participant failure relate@

Proiect manager% abilitylwillingness to meet obligations 1 Labour lniuriesfaccidents

Proiect manager's abilitylwillingness to meet obligations

Projecr manager's abiiitylwillingness to meet obligations

Proiect manager% abiiitylwillingness to rneer obligations

Proiecc manager's abïiîtyfwillingness to meet obligations

Contract Clauses Irisk to contractor. shared. owner bears riskl

Contract Clauses [risk t o contractor. shared. owner bearsrisk)

toni ract Clauses [risk to contractor. shared owner bearsrük)



Presence of a cooperarivefparmering environment

Contract Clauses [risk to contractor. shared. owner bears risk]

0 4 5 0

1 4 4 0

O 1 4 4

1 Scope creep

1 ~ o s t overrun

Construction claims

Contract Clauses [risk to contractor. shared. owner bears risk) ( Project manager's abilitt~iwillingness to meet obligations ( 3 ( 3 ( 2 ( O

2 3 3 1

1 5 3 0

3 3 1 2

1 Design changes

Vork stoppages

Contractor Payment Type [lump. unit. guaranteed max. etc.]

Contractor Payrnenc Type [lump. unit. guaranteed mai. etc.]

Cost overrun l 6 1 2 l o l 1

Construction daims I s I 4 l O l o

4 , 4

Construction Procurement [design build, CM. etc.)

Construction Procurernent (design build, C M etc.]

Construction Procurement (design build. CM. etc.]

Proiect manacier's famiiiafitu with tuue of wark

5 4 0 0

1

Contractor Payment Type [lump. unit. guaranteed mai. etc.]

Contractor Payment Type (lump. unit. guaranteed mai. etc.]

Contractor Payment Type [lump. unit. guaranteed max. etc.)

Contractor Payment Type [lump. unit. quarantecd max. etc.]

Construction Procurement (design build. CM. etc.]

Construction Procurement [design build, CM. etc.)

Construction Procurement [design build. C M etc.)

O

Unbudgeted overtime

Proiect manager budget correcting rneanires

Proiect manager's abiiityfwiflingnesr to rneet obligations

Contract dauses

Construction claims

Coordinaiion of Trades

Presence of a cooperativelpartnering environment

Project manager's abilityfwillingness to meet obligations

Contract clauses

Contractor Paymcnt type

Unbudaeted overtime

Proiect manager's tarniliarity with type o f work

Proiect manager% famiiiarity with typeof uork

ConstructionlOperations Interference Problems (Coordination of Trades

3

3 1 2

Project manager's knowledge of geographical area

ConstructionfOperations Interference Problems

ConstructionlO~erations Interference Problems

CanstructionlOperations lnterkrence Problems ( Work stoppages

Proiect manager% familiaritg with type of wark

- - -



3

2

1 4 2 2

1 3 1 3

2 6 1 0


Construction deldys (not participant failure related]

Labour ~roductivitu

- -

CanstructiontOperations lnterference Problems MaterialfEquipment Loss

1

-

ConstructionfOperations Interference Problems 1 Labour Iniuriesfaccidents

6 2 1 0

5 4 0 0

2

0 5 3 1

3 3 1 1

1 7 1 0

2 5 1 1

O

3 1 2 0

1 3 5 0

ConstructiontOperations Interference Problems 1 Materials delivery to site uncertainty

Ability to secure prowct site

Ability ta secure proiect site

O

-

ConstrucÜcnfOperations Interference Problems

Abiiity ro secure project site

Abiiity to secure project site

Ability to secure proiect site

Traffic congestion onlaround site

1 3 5 0

1 2 4 2

2


--

Traffic corigestion onlaround site

Traffic congestion oniaround site

Traffic congestion anfaround site

Traffic congestion onfaround site

Amount o f Site accessfegress

Amount o f Site accesslearess

Arnount of Site accesslegress



3 3 2 1

5

0 4 5 0

l ~ o r k sto~oaaes l l l ~ l ~ l O

2

Materials delivery to site uncertainry

MateriallEquiprnent Loss

Labour Iniurieslaeeidents

Constroetion~Ooerations interference ~roblems

Labour productivity



4

ConstiuctionlOperations interference prablems

Ability to secure project site

Labour ~roductivitu

Belief Nenvork Anabsis of Direct Cosr Risk in Building Consfntction 110

-

1 1 4 0 1 7

0 5 3 1

0 7 2 0

2 4 3 0

Materialsdelivery to site uncertainty

ConstructionfOperationsinterference problerns


TraRic congestion oniaround site

5

1 6 1 1

4

1

-

2 7 0 0

1 1 4 3

O

0 7 2 0

O

1

O

--

1 5 3 0

0 5 4 0

1 2 5 1

0 1 4 4

Permitting Requiroments

Perrnitting Requirernenis

Permitting Aequiternents

Number OF workers on site

Nurnbcr o f workers on site

Nurnber of workers on site

Nurnber of workers on site

Nurnber of uorkers on site

Number o f workers on site

Nurnber o f woriers on site

Nurnber o f workers on site

Nurnber o f workers on site

Environmental Hatards

Environmental Hazards

Enuironmental Hazards




Environmental: Hazards



New technology requirements for construction

BeliefrWwork Anaipis of Direct Cost Risk in Building Cons~nrction 11 1

Regulatonj penalties

Labour Iniurieslaccidents

Contract clauses

Labour productiviig

Oefective work - rnistakes


New technoloqy rtquirements for constructian


New technology requirementsfor construction

New technologg requirements for construction



New technalogy requirements for construction

New technologg requirements for construction


CompleritylConstrucUbility of design

CornplewiiylConsiructabiIity of design

Compleniq!Constructabiiiq of design

ComplenitylConstructability of design

ComplewitylConstructabilirg of design

ComplexitylConstructability of design

ComplewitylConsWctability of design

CornplewitylConstructabiIity of design

ComplexitylConstructability of design

CornplexitylConstructability of design

ComplewitytConstructability of design

CornplewitylConstructability of design

CornplenitylConstructability of design

CamplewitylConstructability of design

Complewity~Const~ctabiiity of design

Coordination of design teams


Coordination of design tearns


Coordination of design tearns

3 1 5 0

8 1 0 0

1 5 3 0

2 6 1 0

6 3 0 0

3 4 1 1


Labour Iniuriestaccidents

ConstructiontOperations interference problerns

Abilitg to secwe project site


Amount of site accessleqress

Unbudgeted ouertime

Construction delays (not participant M u r e relate4

Labour productivity


Work stoppages

Equiprnent productivity


Contract clauses

Perrnitting requirements

Unbudgetad overtime

2 6 1 0

0 6 3 0

2 5 1 1

1 4 4 0

0 2 5 2

1 5 2 1

4 3 2 0

O 4 4 1

1 6 2 0

2 2 3 2

1 2 3 3

2 5 2 0

2 3 4 0

0 5 4 0

2 3 2 2

3 5 1 0 -- --- -

Construction delags (notparticipant failure related]

Labour productivity

Defective work -mistakes

Labour lniuriesiaccidents

Contract clauses

Proiect manager's farniliariry with type of work

Perrnitting requirements

Number o f workers on site


Unbudgeted overtime


Labour productiuity



Design changes

Equiprnent productivity

Labour lnjurieslaccidents

Tirneliness of design

Quality of design

Completenessof design

Contract clauses

Permitting requirernenrs

Number of workers on site

New tcchnology requirements for construction

Design changes

Tirneliness of design

Quality of design

Completenessof design

Scope creep

2 5 1 1

0 4 4 1

0 3 4 2

0 2 2 5

0 1 4 4

0 3 4 1

0 7 2 0

1 5 2 1

1 5 1 2

4 5 0 0

1 6 2 0

0 2 7 0

3 6 0 0

3 5 1 0

7 1 1 0

3 2 3 1

2 1 6 0

1 3 3 2

0 5 2 2

O 3 4 2

0 4 4 1

1 4 4 0

3 5 1 0

2 2 4 1

1 5 1 2

1 5 2 1

2 5 2 0

5 4 0 0

0 0 5 4

Available qudified key proiect management personnel Work stappagw + 3

Auailable qualitid key proiect management personnel

Auailable quafifiid key proieet management personnel

AvaiJable qualified key proiect management personnel

Available quaGfied key proiect management personnel

--

Private or Publicly funded iob

Private or Publicly funded job

Private or Pubiicly funded iob

Private or Publiclu funded iob

Construction claims

Tünelmess of cost repartinglaccounring


Coordination o f Trades

Available quatified key prokct management personnel

Auailable qualified key proiect management personnel

Available qualified key proiect management personnel

Available qualified key proiect management personnel

Available qualified key project management personnel

Auailable qualified key p ro je t management personnel

Auailable qualified key proicct management personnel

Available construction support faciüties (housing. e t c ]

Available construction support facïlïties (housing. etc-]

Auailable construction support faclties (housing. etc.)

Available construction suppoit faclties (housing. etc)

Private o r Publicly funded iob

- --

Construction rnatket prier cscalation

Construction market price escalation

Construction matket mice escalation

0 1 5 3

1 2 4 0

1 5 3 0

1 2 4 2

Presence of a cooperativelpartnering environment

Proiect manager's abilitglwilhgness to meet obligations

Construction procurement

Proiect manager's famiridrity uith type of work

Project manager's knowledge of geographical area

Const~ctionlOperations interference problems

Coordination o f design tearns

Labour productivity

Work stoppages


Nurnber of workers on n'te

Construction claims -

1 Budget revisions allowed

Contract c lauss

Contractor Payment type


Belie f Nenvork Analysis of Direcf Cost Risk in Building Constnrction 112

O

3

O

O

O

2

3

3




Other maior construction aetivitg in area

Other maior construction activity in area

Other major construction activity in area


Other major construction accivity in area

Other maior construction actiuity in area

Other maior conscntction activity in area

Olher maior construction activity in area

Owner financial stabiiïty

Owner financial stabiMy

Owner financial stability

Owner financial stability

Physical proiect site

Physical proiect size



Physical project site

Physical project size

Physical proiect sRe

Physical proiect sire

Competing activity o n site

Campeting actiuity on site

Competing activity on site

Cornpeüng activity o n site

1 1

2

2

I l

2

3

1

1 6

6

1 4

4

5 -

1 5 2 1

1 6 2 0

2 3 3 1

5 1 3 0

-

- - ---

Proiect manager budget correcting measures

Cost of materials

Budger revisions allowed

Cost of materials

Materials delivery to site uncertaintg

Adequate quantity OF quaiity materials in area

Avaiiability of suitable equipment

Availability of quabfied key labour personnel

Available qualified key proiecc management personnel

Available construction support

Construction market pnce escalation


Contract clauses

Contractor Payment type


Construction delags [not participant failure relateq

Labour productivity



Ability t o secure proiecl site


Amount of site accessfegress

Permitting requirements

Construction delays [not participant failure related)

Labour productiuity


Equipment productivicy

Cost ouerrun

Cost of equipment 1 0

Cost of labour i l

1 3 4 1

5

2

3

3

1

3 --

1 -

3 -3

3 6 0 0

0 6 3 0

0 5 4 G

1 2

0 2 5 2

1 2 4 2

1 5 3 0

1 7 1 0

0 5 3 1

0 3 5 1

O 0 0 1

O 0 5 4

0 5 3 1

1 1 6 1

0 4 4 1

1 3 3 2

3 1 3 2

3 3 2 1

3 4 2 0

3 4 2 0

0 4 3 2

4 3 2 0

0 6 2 1

1 3 4 1

2 3 4 0

3 3 3 0

1 5 3 0



Competing actiuitg on site

Compethg actiuity on site

Competing a&vity on site





Availability of energy

Availability o f enrrgy

Auailabilitg of enrrgy


Avaiiability OF energy



Presence!location OF utilities

Presencellocation of utilities

Pfesencellocation of uiilities

Presenceflacation of utiiities

Presencellocation of utilities

Presenceflocatian of utilicies

Prcsencellocation of utilities

Presenceflocation of utiliries

Presencelloution of utilities

General area affluenceluealth

General area affluenceiweakh

General area affluencefwealth

General inflation

General inflation

General inflation

O

3


ConstructionlOperations interference problems



Amount of site accessfegress

Permitting requirements



ComplenitylConnructability of design

Cost of equipment

Construction delays (not participant failure rrlated]

Labour praductivity

Cost of materials

Use of foreign purchased materialslequipment


New tecfinology requirements for construction


Eauiornent oroductiuitu

General inflation

General inflation

General inflaiion

General inflation

General inflation

Arnount OF government spending o n construction

Amount of government spending o n construction

Amount of governrnenc spending o n construccion

Amount of gouernment spending on construction

Tax Rates

Belief Nenvork rlnalysis of Direct Cosr Risk in Btrilding Consrnrcf~on 113

Labour hiurieslaccidents


Perrnitting tequirements

Enuironmental Harards

New technology rrquirements for construction

ComplerityConstructability of design

Auailability of energy

Traffic congestion onhound site

Available consiruction support

Private or publicly funded iob

Cost overrun

Cost OF equipment

Cost OF labour

Tdx Rates

Tax Rates

Tan Rates

fan Rates

Tan Rates

Tan Rates

Tax Rates

Exchange Rates

Exchange Rates

Ewchange Rates --

5 4 0

6 2 1

3 3 2

2 4 2

1 3 5

1 3 4

1 6 2

4

3 2 4

0 4 4

0 5 4

4 4 1

7 2 0

6 2 1

5 2 2

2 4 1

1 5 3

4

Project manager budget correcting measures

Cost of materials



General area affluencefwealth

Private or publicly funded iob


Other major construction activity in area

General inflation

Cost overrun

4

2

2

-- -

Cost of equipment

Cost of labour

Project manager budget correcting measures

Cost of materials

Other maior construction activity in arra

General area affluencelwealth

General inflation

international market-related price increases

Use of Foreign purchased materialslequipment

General inflation

0 5 3 1

2 2 3 1

3 2 3 0

3 6 0 0

4 1 3 1

6 1 2 0

4 3 1 1

2 3 3 1

0 0 5 4

0 2 3 4

2 2 5 0

5

2 6 1 0

1 6 1 1

0 1 5 3

3 2 4 0

4 1 1 0

1 2 3 3

1 2 5 1

1 2 6 0

2 7 0 0

4 2 3 0

4 2 1 2

0 4 3 2

1 5 2 1

5 3 1 0

O

5 0 2 2

5 3 1 0

0 4 3 2

4 5 0 0

0 6 2 1

0 4 2 2

0 3 3 2

2

Belref Arenvork Analysis of Direcr Cosr Risk in Building Consrrirction 114

. .-

Stabilityfsophistication of government

Sabilitylsophistication o f government

Stabfitytsophistication o f govemment

Stabilitglsaphisti~tion o f government

StabilihJlsophtication of governrnent

Stabilityhophistication of government

Land refated natural d i s t e r (Iandriide. earthquake. etc)

Land related natural dirasier (landsiide. earthquake. etc]

Land related natural disascer [landslide. earchquake. etc]

Land related natural disaster [landslide. earthquake. etc] -

Land related riaturai dwster [landskde. earthquake. etc]

Land related natural disaster [landsiide. earthquake. etc]

Land related natural disaster [landslide. earthquake. etc]



Land related natural disaster [landslide. earthquake. etc]

Land relatcd natural disaster [landsiide. earthquake. etc)

Site Topographg

Site Topography

Site Topagraphy

Site Topagraphy

Site Topography

Site Topography

Site fopography

Site Topography

Potential for Weather Entremes

Potentialfar Weather Extremes

Potential for Veather Entremes

Potential for Weather Ewtremes

Potential for Wealher Extremes

Potential for Weather Ewtremes

Potential for Weather Enrremes

Potential for Weather Extremes

Potential for Weather Entremes

Patential for Weather Entremes

Usual clirnate

Usual climate

Usual climate

Usual climate

Usual climate

Usual climate

Usual climate

Usual clirnate

Usual climate

Usual climate

Usual climatc

Geography turban proiect. rural. remote]

Geography (urban project. rural. remote]

Geography (urban proiect. rural. remote]

Geography (urban proiect. rural. remote]

Geography (urban project. rural. remote]

2 3 4 0

2 2 3 2

0 4 2 3

0 4 I l

1 2 3 3

1 3 2 3

0 0 5 4

3 3 2 1

5 4 0 0

6 3 0 0

3 4 1 1

6 2 1 0

1 5 2 1

1 4 2 2

O 7 1 1

0 4 5 0

1 3 2 3

2 4 3 0

1 4 4 0

3 4 2 0

3 3 2 1

3 4 1 1

3 4 2 0

2 5 2 0

2 3 4 0

1 2 6 0

0 2 7 0

3 6 0 0

O 8 1 0

2 5 2 0

0 9 0 0

3 3 2 1

3 5 1 0

3 4 2 0

1 1 6 1

6 1 1 1

5 1 3 0

5 1 3 0

4 4 1 0

3 3 3 0

2 1 2

Régulatory penalties

Perrnittmg requirements

Private o r publicly funded iob

Amount a f gouernment spending on construction

Taw rates

Exchange rates


Labour productivity

Cost o f materials

Material Vaste


Adequate quantity of quility materials in area

Availability o f suitable equipment

MateriallEquipment Loss




Labour productivity




ComplewitytConstructability of design

Physicdl proiect size

Presenceflocation of utilities

Land reiated natural disaster

Unbudgeted ouertime

Construction delays [not participant failure related)

Material Vaste

Materials deliuery to site uncertainty

MaterialtEquipment Loss

Labour lnjuriesfaccidents

Environmentat Hatards

ComplewityiConstructabilÎty of design

Auailability of energy

Land related natural disaster

Unbudgeted overrjme

Construction delays (not participant failure related)

Labour produciivity



Labour Injurieslaccidents



Comp:exi~yfConstructabilitq of design

Land related naturai disaster

Patential for weather entremes

Cost of equipment

Cost of labour

Labour productivity

Cost of materials

Materials delivery to site uncertaintg

----

2

5 3 1 0

5 3 0 1

3 5 1 0

5 3 1 0

3 4 2 0

3 1 4 1

2 3 3 1

0 1 7 0

5 2 2 0

3

1 5 3 0

Geogfaphy turban project. rural. remote]

Geography turban proiect r u r d remore)

Geography [urban proiect. niraï. remote]

Geography turban proiect. rurai. remote)

Geography turban proiect. mai. remote]

Geography (urban proicct. rural. remote]

Geogaphy [urban proiect. rural. remote]

Geography [urban proiect. ~ r a l . remote]

Geography (urban proiect. rurai. remate)

Geography (urban project.rural.remote]

Geography [urban proiecr. rural. remote] - -

Geography [uiban proiect. rural. remore]

Altitude

Altitude

Altitude

Altitude

Altitude

Altitude

Altitude

Altitude

Aitirude

Altitude

Altitude

Altitude

Altitude

4

Use of foreign purchased materialdequipment


Auailability o f mitable equipmenr

Auailability of quaiified keg labour personnel

Proiect manager's knouledge of geographical area


Phyr ia l praject size

Auaiiability of energy

Presenceflocation oF utilities

General area affluenceluealth

Potential for weather ertremes - - .

Usual climate

Cos; of equipment

Cost of labour

Altitude

Altitude

Altitude

Geolagy

Geolagy

Labour produciiuity

Cost of materials

Materials deliuery to site uncertainty



New technology requirements for constructian

ComplenitylConstructability of design

Avdilability of energy

Presenceilocation of utilities

Land related natural disaster

Site :opography

-

Geobgy

Geology

Geoloau

2

4 3 1 1

5 3 1 0

3 6 0 0

6 2 1 0

6 2 1 0

5 4 0 0

5 3 1 0

4 2 3 0

4 3 2 0

2 5 2 0

3 1 4 0

Potential for weather extremes

Usual climate

Geography

Cost of equiprnent

Unbudgeted overtime

--

Geology

Geology

Geology

1 3 4 1

3 5 1 0

4 2 3 0

2 3 3 1

3 2 4 0 - -- -- - -

Construction delaystnot participant failure relate4

Labour productiuity

Cost of materials

Geology

Geology

Geology

Geology

Geology

Geology

Geology

Geology

Geology

BeliejA'envork .Inalysis of Direct Cosr Risk in Building Consfnrcfion 115

6 1 2 0

2 3 3 1

0 5 2 2

3 4 2 0

2 3 4 0

4 3 1 1

4 3 2 0

0 5 2 2

3 3 2 1

4 4 0 1

3 2 2 2

5 3 1 0

5 2 2 0

2

- -- - -

Design changes



Geology

Geology

-

0

0 0 7 2

2 2 4 1

7 1 1 0

1 1 6 0

7 1 0 1

3 1 5 0 -

Oeviation from erpected quantities of work


Enuironmental Harards

New technology requirernents for construction

CompleritylConstructabiliiy of design

Auailability of eneigy

Presencellocation of utiiities

Land related natutal disaster

Site topography

-

Geography

Altitude

2 2 3 1

3 3 2 1

6 2 1 0

1 1 7 0

0 1 5 3

3 4 2 0

5 2 2 0

1 4 4 0

6 2 1 0

4 3 2 0

0 1 5 3

Appendix D: Divorcing

Belief Nenrork .4nalysis o j Direcf Cosf Risk in Blrikiing Consrruction 116

Labour Productivity Divorcing

ed key Labour Pe iuctionlOps lnterfe

Construction Delays Divorcing

Behef ~Vefivork Anuiys~s of Direct Cosf Risk in Building Consrnrctcon 117

Construction Claims Divorcing

Appendix E: Asymmetric Assessrnent Structures

Belief iVenvork Anaiysis oJDirec! Cos! Risk in Building Cons!nrcrion 119

Asymmetric Assessment: Construction Delays

Construction Delays Parents: Environmental Deiays Participant Failure Delays Design Delays Logistics Delays Labour Delays

Asymmetric Assessment Structure:

+ Environment Delays + Major X + Minor or None + Participant Failure Delays

3 Major X 3 Minor or None

3 Design Delays + Major + Logistics Delays 3 Major

3 Labour Delays + Major X 3 Minor or None X

-3 Minor or None 3 Labour Delays + Major X + Minor or None X

+ Minor or None + Logistics Delays Major + Labour Delays + Major X

4' Minor or None X + Minor or None 3 Labour Delays

3 Major X 3 Minor or None X

10 probabilities required in total (marked with an X)

Bzlief Senrork .4nalysis of Direct Cost Rirk in Building Consrnrcrron 120

Asymmetric Assessment: Work Quantity Deviations

Work Quantity Deviations Parents: Design Changes Defective Work Change in Tenant Requirements Ground Conditions Design Quality


+ Design Changes 3 Major X 3 Minor or None + Defective Work + Major X

3 Minor or None 3 Change in Tenant Requirements

-3 Major + Ground Conditions + Worse than Expected + Design QuaIity + Poor X + Good X

i As expected or better + Design Quality + Poor X i Good X

+ Minor + Ground Conditions -3 Worse than Expected + Design Quality

3 Poor X -3 Good X

+ As expected or better + Design Quality + Poor X + Good X + None + Ground Conditions

3 Worse than Expected 3 Design Quality

3 Poor X + Good X i .4s expected or better + Design Quality

3 Poor X i Good X

14 probabilities required in total (marked with X)

Asymmetric Assessment: Project Material Shortage

Project Material Shortage Parents: Design Changes MatenalEquipment Loss/Damage Materials Delivery Promptness Material Waste

Asymmetrïc Assessment Smcîure:

+ Materials Delivery Promptness -3 Frequently Late X + Generalty On Time

i Material Waste + Major + MaterialdEquipment Loss/Darnage

3 Major --) Design Changes

+ Major X 3 Minor or None X + Minor or None

+ Design Changes 3 Major X 3 Minor or None X

3 Minor or None + MaterialdEquipment Loss/Damage

-3 Major + Design Changes

Major X + Minor or None X

3 Minor or None Design Changes

3 Major X Minor or None X


Belief ~Vehvork =lnafysis of Direcr Cost Risk in Bzdding Consrniction 122

Asymmetric Assessment: Suitable Equipment Availability

Suitable Equipment Avaitability Parents: Project Geography Local Construction Market Saturation Materials/Equipment Loss/Damage

Asyrnrnetric Assessment Structure:

+ Local Construction Market Saturation + Saturated X -9 Some Other Construction

9 Project Geography + Remote X + Urban

+ MateriaIsEquipment Lossrnamage 3 Major X 3 Minor or none X + Rural

+ MateriaIsEquip ment Lossrnamage + Major X Minor or none X + Area Consûuction Poor + Project Geography + Remote X + Urban

3 Materia WEquipmen t Lossrnamage 3 Major X -3 Minor or none X + RuraI

3 Materials/Equipment Loss/Darnage + Major X i Minor or none X

1 1 probabilities required in total (marked with X)

BelÏe/:Venvork ilnalysis of Direct Cost Risk rn Building Consrnrcfion 2 23

Asymmetric Assessment: Traffic Congestion odaround site

T r a c Congestion Parents: Site Access/Egress Number of Workers on Site Competing Activity on Site Physical Project Size


+ Physical P r ~ j e c t Size + SrnaIL + Competing Activity on Site + Yes X + No

Nurnber of Workers on Site + Person Congested X 9 Not Person Congested

3 Site AccesdEgress i Insuficient X + Adequate X

3 Large Cornpeting Activity on Site + Yes + Number of Workers on Site

3 Person Congested + Site Access/Egress + Insufficient X

i Adequate X 3 Nor Person Congested

i Site Access/Egress 3 lnsuficient X 3 Adequate X

i No i Number of Workers on Site

Person Congested Site Access/Egress + Insufficient X

3 Adequate X 3 Not Person Congested

i Site AccesdEgress + Insufficient X 3 Adequate X


Belief Nenvork Anabs is of Direct Cost Risk in Building Cons~niction 124

Appendix F: Cornparison - Probability Survey Interpolated Values to Survey

Values

Beliej'.Venrork Anaiysis of Direcl Cos[ Risk in Building Constnrcrion 125

Labour Productivity Interpolated - Surveyed Value Comparison

Ranking 1

4 5

Polynomial: Rsquared = 0.73 90 -4

Suweyed Average 90

Comparison

Combination Suweved

85.6 83.1

Combination Surveyed

Combinat ion Suweyed

8 9 10 11 12 13 14 15

I

State Combination

16

---- ----- O Labour Productivity Trend Line P o l y . (Labour Productivity Trend Line)

90 90

73.3 69.2 64.7 59.7 54.4 48.6 42.4 35.8 28.8 1 20 1 combinat ion Surveyed

Belief Nenvork Anaipis of Direct Cost Risk in Building Construcfion 126


70 50 60 60 50 70 40 40

Work Quantity Deviations Interpolstted - Surveyed Value Comparison

Ranking 1 2 3

Exponential [Rsquared = 0.59) 81 -4

4 5

Tl -9 63.5

6 7 8 9 1 0

Comparison

Suweyed Average 90

56.1 49.6

State Combination

Combination Surveyed 30 90

43.8 38.7 34.2 30.2 26.7 - -

PP

+ Work Quantity Deviation Trendline ,

Combination Surveyed Combination Surveyed

80 50

- -

40 20 20 10

11 12 13 14

- Expon. (Work Quantity Deviation Trendline) '

Cambination Sutveyed

40 40 30 30 30



23 -6 20.9 18.4 16.3

Belief Nemork Analysis of Direct Cosr Risk in Birrlding Constnrcfion 127


SuitabIe Equipment Availability Interpolated - Surveyed Value Comparison

I I -- I

5 1 53-4 1 40 1 Combination Suiveyed

Ranking 1 2 3

I I . - 1

11 1 40-2 1 40 1 Combination Surveyed

Logarithmic (Rsquared = 0.67) 80.3 68.7 61 -9

6 7

Comparison

State Combination

Surveyed Average 90

50.3 47-7

---- - - -

Suitable Equipment Availability - Log. (Suitable Equipment Availability) -- - - - -- -- - - -- - -- - - ---- --


50 50

Belief h'envork Analysis of Direct Cosr R I S ~ in Bttrlding Constntction 128

8 9

60 60

60 An

45.5 43-5

Combination Surveyed Combination Surveyed

Combination Sutveyed

Appendix G: Probability Curves

Belirf Nenvork rlnnlysis of Direcr Cos1 Risk rn Building Consrrucrion 2 29

Probabiiity Curves

8 Child States, 16 Parent State Carnbinations, Standard Deviation = 2.5

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16

Parent Probabllity Combination Ranking

Source Data

Worst Cas€

Best Case

LIelieJNenvork Anaiysis O/ Direct Cost Risk in Building Consrrucrion 130

Appendix H: Predictor Variable Ranking

Belief Nenvork rlnalysis of Direct COSI Risk in Budding Cons~mc~ion 131

Labour (nst Variable Parent State Rankinq I Parent Variables: Qualified Local Labour inflation Project Geography

Labour FraductMty Overtirne Canstrucîion Delays

Parent Variables: Qualified Local Labour Inflation Projecl Geaqraphy Labaur Productmty Cvertime Constmction Delays

Belief Nenvork Analysis of Direcr Cost Rrsk in Building Cons~nrcfion 132

Labour Cost Variable Parent State Rankinq

Parent Variables: Qualied Local Lahour inRation Projert Geography Labour Productmty Overtime Construction Delays

Parent Variables: Qualified Local Labour inflation Project Geography Labour Product~ty Clvertirne Construction Delays

Belief Nenvork Analysis of Direct Cost Ri& in Btrilding Constnmion 133

Variable State:

4

2 1

Ge~graphy (1 .a) , R e m e

3 X X X X

X

X

Lsbaur ~2.561 hsufficient

X X

X X X X X X X

Rurd

X X

X

~deauate

X

1 PrOdudivPy (2.56) Urfxm

X

=Expected

X X X

X X X X X X

-Erpeded

X

X X X X X

X X

c=Emeded

X

X

=Expected

X

-Expected

X

Deiavr C2.2222)

IX 1

cbpecied

X X X X

X X X X

m m

X X X X

X X X X

Score Minar

X

X

10.50 10.84 11.10 11.10 11.10 11.44 11.78 11.78 12.72 13.66

12.30 12.70 13.00 13 .00 , 13.m 13.40 13.80 13.80 14.90 16.00

Parent Variables:

Parent Variabks:

Eauinment Cmt Variable Parent State Rankinq

Suitable Equipment Availability Inflation Value Engineering Construction Market Escalation Equipment Pmductmty Construction Claims

Suitahle Equipment Availability Inflation Value Enqineerinq ~onstructi~n Market ~scalation Equipmenl Productrvity ~ o n s t ~ c c o n ~ l a h s

Belief Nenvork Anafysis of Direcc Cos! Risk in Btrilding Constnrc!ion 134

Faui~ment Cnst Variable Parent State Rankinq

Parent Variables: Suitable Equipment Amilabiiity Inflation Value Engineering Construdion Market Escalation Equipment Prnductkty ConstrriMion Clairns

BeliefrVenïork Analysis of Direct Cosr Risk in Bdding Consrnrction 135

State: 4 3

1

h s u t r i

X X X X X X

~deguatc

X e ~ e d l -

X X X

X X X

X

*tirpected) -tipecttci J*hpeded --~rpectcd..

X

X

X X X X X

X

-

X X

X X X X

MOW ( MYX

X 1 ~d ~ a d i ~ d

X X X X X

X

X X X

X X

X

Prsdiled

X _

Score 8.20 1 1259 0.64 8.67 8.75 8.92 8.92 10.42

13.27 13.31 13.44 13.70 13.70 16.00

Material Cost Variable Parent State Rankinq Parent Variables: Construction Market Escalation Scope Creep Material Shortage

Design Changes Material Waste Value Engineering

Parent Vanables: Construction Market Escalatron Scope Creep Matenal Shortage Design Changes Mafenal Waste Value Engineenng

Pare Variabl -

Star

Score 13.00 0.00 1.50 2.79 1.67 2.44 1.89 2.76 1.89 2.76 200 2.92 200 2.4 3.17 4.63 3.39 4.95 3.39 4.95 3.50 5.1 1

ire 7.88 7.88 7.96 8.04 8.12 8.12 0.12 8.12 8.28 8.45 8.45 8.61 8.61 10.16 10.32 10.32 10.32 10.32 10.48 10.64 10.64 113.80 10.m 10.89 10.89 11.05 11.05 1 1.37 - 13.08

Belief r\renuork Ana[vsis of Direcc Cost Risk in Building Consrrtrcrion 136

Appendix 1: Probability Survey Results, Prior Probabilities

ID#

f 1

2

5

Cause

Poor P M cIaims mitigation Major Field C l a h

Major Oelay C l a h

Major Design Ctaims

Good P M cbims mitigation Maior Field Claims

Maior Delay Claims

Maior

Poor PM ckims mitigation Maior Field Clairns

Minor or no Delay Claims

Major Design Clairns

6

7

1 Effect

Maior Construc~ion &rns

Maior Construction Clairns

1

Maior Construction Clairns Good PM claims mitigatian Minor or no Field C la im

Maior Delay Claims

Maior Design Clairns

8

9

Belief ~Vefivork Rnalysis of Direct Cost Risk in Building Constnrction 139

3

4

Major Construction Clairns

Good PM clairns mitigation Major Field Claims

Major Delay CIaims

Minor or no Design Claims

10

-- ----

90

80

40

Poor P M clairns mitigation Minor or no Field Claims

Maior Oelay Claims

Minor or no Design Clairns

Good PM clairns rnitigation Maior Field Clairns

Miior or no Oelay Claims

Maior Design Claims

-5

70

40

80

70

Poor P M claims micigaiion Minor or no Field Claims

Maior Oelay Claims

Maior Design Claims

Paor PM clairns mitigation Maior Field Claims

Major Delay Claims

Mmor or no Design Claims

80


Poor PM clàirns micigation Minor or no Field Cloims

Minor or no Delay Clairns

Maior Design Claims

80



Expert

1 2 3

100

70


Maior Construction Claims

70

70

40


100

80

80

50

60

90

40

70

80

70

70

70

60

50

80 50

Cause 1 . Expert

11 Poor PM clairns mitigation m i o r Canstruction Claims

Maior Field Clain.

Mnor or no Delay Clairns

M ï o r or no Design Uaims

12 Gaod PM claims mitigatian Maior Canstruction Claims

Minor or no Field Cbims

Maior Oclay Clahs

Minor or no Oesign Clairns

-- 13 Good P M clairns mitigatian Maior Construction Claims

Minor or no Field Claims

Minor or no Oelay Claims

Major Design Claims

14 Good P M daims mitigation Major Construction Clairns

Major FreId C!+ms Minor or no Delay Claims

Minor or no Design Ciaims

15 Poor P M claims mitigation Maior Construction Claims

Minor or no field Claims

MÏnor or no Delay Claims

Minor or no Design Uaims

16 Good

Miior or no

Minor or no

P M cldrns mitigarion

Field Ciaims

OeIay Claims

Major - -

Conslruction Clairns

6 1 Major Construction Delays

Worse than Ewpected Labour Productivity

Overtime

Prescnce OF ~ c o p e Creep I I I I

2 Maior Construction Oelags 1 >expected Overtime

Worse than Erpected Labour Productivity

No Scopr Crrrp

I

3 Maior Construction Oefays > eupected Overtime 80 70 80

As crpected or better Labour Productivity

Presence of ~ c o p e Crrep I I I I

I I I

4 Maior Cornrucrion Delays > expected Overtime BO 70 80

As erpected or beaer Labour Productiuky I I I 1 NO scope Creep I I I I

5 Mino:or no Construction Delays

Vorse than Expected Labour Productivity I --

>erpected Overtime

Presrnce ot Scope Cretp I I I I I I

Belief Xenvork Rnalysis of Direct Cosr Risk in Brdding Conmrcrion 140

ID#

7 j ~ m r a r n o Construction Debys 1 >expected Overtimc 1 30 1 20 1 40 1 30.0 1

Cauzc Elfcct Enpeit Value I 6

1 AS expected ar bctter Labour Producrivirg t 1 1 I I I (Ptesence of Scope neep I I I I I I I

Minoror no Connruction Delays

Voise than Ewpected Labour Productiuitg

No Scope Crcrp

7 1 (Reactive Proiect Manager 1 Untirnely Cost ReportingfAccounting 1 90 1 90 1 80 1 86.7

I I I I I

>ewpected Overtime

8

8 1 ( Maior Environmental Oelays Construction Drlays

I I I I I I

1

60

Minororno Construction Oelays

As eupectcd or bettrr Labour Productiuity

2

2

60

> ewpected Overtime

3

Minoror no Environmental Delays

Maior Participant Failure Oelays

4

3

60

20

Maior Labour Delays

Major Logistics Oelays

Major Design Oelags

Minor or no Environmental Oelays

Minor or no Participant Failure Oelays

( Minor cr no Participant Faiiure Oelaqs 1 1 1 1 1

Used

60.0

Major Construction Delays

Minoror no Labour Oelays

Major Logistics Oclays

Maior Design Delays


Minor or no Participant Failure Oelags

I

6

Behef ~Venvork rlnaiysis oJDtrect C o s Risk in Btrtlding Construction 141

10

Maior Construction Oelays

Major Construction Delays 5

100


Major Labour Delays

Minor or no Logistics Delays

Maior Oesign Delayr

Minar or no Environmental Delags

Minor or no Participant Failure Delags

Major Labour Delays

Maior Logistics Delays

Minar or no Design Delays


1

80

80

100

BO


10.3

100

70

1

100

90

80

100.0

BO

70

86.7

80

73.3

80

83.3

70 76.7

I 7 Minororno Labour O e b p Major Cansuuction Oolays

Mmor or n o Loginics Oelays

Maior Design Dclagr

1 *or or no Environmental Oelays 1 ( ~ i n a r or no Partffiipant Faaure Delays 1 I 1

I

8 Minororno Labour Oelays Maior Construction Delays

1 Maior Logistics Oelays I 1 ino or or no Design Delays I 1 Minor or no Environmental D r l a p

1 Minor or no Participant Failure Oelaÿs 1 1 I

- -

Labour Oelays 1 ~ a @ r Consmction Oelays

togistics Delays I 1 Minor or no Design Oelags 1 1 ino or o r no Environmental Oelays 1 1 Minor or no Participant Failure Delags 1 1 I

10 Minor or no Labour Delays

Logistics Oelaps

Design Oelays

Environmental Oelays

Maior Construction Delays

15 1 )frequent Short breaks 1 terpected Labour Produc;ivity

Major Labour Congestion

Major Oehctive SZark

Poor Labour Design Understanding

2 Frequent

Major

Major

. -

Short breaks

Labour Cangestion

Defective Work

pp

Labour Producriviq

( ~ o o d Labour Design Understanding ) 1 I I 1

3 Frequent Short breaks cerpected Labour Productivity

Minor or no Labour Congestion

Maior Oefoctive Work

Poor Labour Design Understanding

4 Frequcnt

Minor or no

Maior

-

Short breaks

Labour Congestion

Oefectivc Wark

cexpected Labour Productivity

( Good Labour Design Understanding 1 I I

5 lnfrequent Short breaks terpected Labour Prmductivity

Maior Labour Congestion

Major Oefective Work

Poor Labour Design Understandhg

Belief .ficfeni*ork Anabsis of Direct COSI Risk in Btrilding Consrnrcrron 142

Short breaks


Maior Oef ectiue Work

Labour Oesign Understanding

Short breaks

1 Maior Labour Congestion

Minor or no Oefective Work

Poor Labour Design Underscandimg

I 8 lnfrequent Short break

Labour Congestion

Oefectiuc Vork

1 ~ o o r Labour Oesign Understanding

I 9 Frequent

Maior

Short breaks

Labour C4ngestian

1 -or or no Defective Vork

1 Good Labour Design Understanding I

10 lnfregwnt Short breaks

1 ino or or no Labour Congestion

1 ~ a j a r Oefective Work

1 Good Labour Design Understandimg

I

I I Frequcnt Short breaks

1 Minor or no Labour Congestion

1 hninor or n o Oefective Work

1 ~ o o r Labour Ccsign Understandimg

I 1

12 Frequent Short breaks

I Minor o r n o

M i i o r o r n o

Labour Congestion

Defective Work

1 Good Labour Design Understandmg

I Short breaks


Minor o r n o Oefective Wotk

Labour Design Understanding

Short breaks


Minor or no Defective Work

Labour Oesign Understandimg

Short breaks

Mimor or rio Labour Congestion

Minor o r no Oefective Vork

Labour Design Understandmg

cewpected Labour ProductMq

ce~pected Labour Productiviq

cenpected Labour Productivity

- -

r expected Labour Productivitg

texpected Labour Producrivity

cexpected Labour Productivity

c expecred Labour Productivity

:erpected Labour Productivitg

:expected Labour Productivitg

-

:expected Labour Productivity

Belief ~Venvork Analpis of Direcc Cosr Risk in Building Com~rttcrion 143

Short breaks

Labour Congestion

Oefrctivs Work

19 1 Forûiiden Budget revisinns

Reactive Proiect Manager


--

2 Forbidden Budget revisions

Fieactive Project Manager

Minor or no Construction Oelays

3 Forbidden Budget revisions

Proactive Proiect Manager


4

4 Forbideen Budget revisions


Minor or no Construction Oelays

- - - --- -

5 Aflawed Budget revisions

Reactive Project Manager

Maior Construction Delays

6 Allowed Budget revisions

1 fle.uive Project Manager

1 ~ i o r or no Construcrion Oelays

I


8 AUowed


Design Changes l 1 I

2 Minor orno Oesign Changes

Maior Oefective Vork

Design Quality

M i o r Tenant Requirement Change 1 11:~ hn Enpected Ground Conditions

rexpected Labour Producriviq 30 20 30

Uo use of Value Engineering

Uo use o f Value Engineering 40 20 60

Uo use o f Value Engineering

30 use o f Value Engineering

k use of Value Engineering 70 HO 60

JO use of Value Engineering

Io use of Value Engineering 70 50 Sa

1

Io use of Value Engineering 70 70 60

laior Vork Quantity Oeviatians ] 1 90 1 I 100 1 I 90

laior Work Quantity Oeviacions 30 10 30

Minor or n o Oesign Changes

Minor or n o DeFeclive Vork 1 1 1

Belief :Vetwork Analyris of Direct Cosi Risk in Building Construcrion 144

BefieJNehvork Analpis of Direct Cost Risii in Brriiding Constnrction 145

ID#

4

5

6

7

8

9

10

11

Value

Used

83.3

50-0

40.0

50.0

,=

16.7

35.0

Caur

Good Design Quafitg

Maior Tenant Reguuemenr Change Voae thrn Expected Graund Con6itions

Minor or no Design Changes

Mmor or no Defective Work

Poor Design Quafity

Maior Tenant Requirement Change

Asewpecred or better Ground Conditions


Mmor or no Defectiue Wotk

Gaod Design QuaGty

Major Tenant Requiremenc Change

As mpected or beltrr Ground Conditions


Mmor or no Oefective Votk

Good Design QuaLy

Minor Tenant Requirement Change

Worse than Eiipected Ground Conditions


Minor or no Ckfectiue Vork

Poor Design Qualiry

Minor Tenant Requtrernent Change

Vorre than Expected Ground Conditions


Mmor or no Oefeuivc Work

Poor Design Quaty

Minor Tenant Requirernent Change

As eipebed or bertet Ground Conditions:


Mmor or na Oefective Vork

Good Design Qoafiiy

Minor Tenant Requcremenr Change

As enpected or better Ground Conditions


Minor or no Defective Work

Poor Design Quality

No Tenant Requirement Change

Vorse than Enpected Grwnd Conditions

Minor or no Oesign Changes

Minor or no Dcfectiue Votk

1

70

70

40

20

-

00

10

30

fffect

Maior VoikQuantity Deuiations

Major Votk Quantity Oeuiarions

Major Vork Quantity Deuiations

Maior Vork Quantity Drviatians

Maior York Quaniity Ceviarions

Malor Vork Quantiry Deviations

Maior York Quantitg Deviations

Maior VorkQuantity iJevia~ions

Expert

2

100

95

70

SO

70

80

10

-

3

80

55

40

40

30

40

30

40

I Cause I Ulect Enpert

12 1 t o o d Design Quafitg

Tenant Requirement Change

Worse than Erpccted Ground Conditions

Mmor or no Oesign Changes

13 Poor Oesign QuaGty Maior Work Quantity Deuiations 10 - 20

N o Tenant Requirrrnent Change

Ase~pected ar better Ground Conditions


1 ~ i n o r o r no Oefective Wark 1 I 1 I

14 Good Oesign Quality Maior Work Quantity Oeviatians 10 10 10

INO Tenant Requirrrnent Uiange 1 I A r erpected or better Ground Conditions


21 I 1 Frequentiy Lace Materials Derwery Praiect Material Shartage 1 55 1 95 1 90

I I I I I 2 Major Design Changer Frequent Proiect Mattrial Shortagt

Maior MateriallEquiprnent Loss

Generallg an cime Materials Delivery

Maior Materiai Vaste

3 Minor o r n o Design Changes Frequent Project Material Shartage

Maior MateriaIfEquipment Loss

Generally on tirne Materials OeGvery

Maior Material Waste

4 Major Design Changes Frequenr Pioject Material Sitarcage 50 l a 40

Minor o r n o MateriallEquipment Lass

Generailp on timr Materials Deiivery

Beiiej'iVenvork Anolysis of Direcl Cosr Risk in Building Consrntcrion 146

5

6

7

Maior Material idaste

Major DesignChanges

Maior MateriallEquiprnent Loss

Generally on tirne Materials DeGvery

Minor o r n o Material V a s e

Minororno Oesign Changes

Minor or n o MateriallEquipment Loss

Generally on timo Materials Delivery

Maior Material Waste

Minor o r n o Design Changes

Maior MateriallEquipment Loss

Gencrally o n rime Materials Oelivery

Minor or n o Mattrial Waste

Frequent Proiect Matenal çhortagc

Frequent Proiect Material Sharragr

Frequent Proiect Marerial Shortage

50

10

10

10

10

10

50

20

20

2m

13.3

13.3

I Cause fffecc - -

Expert 1 Value!

8

Defeche Work Material Vaste 1 90 1 - 1 90 1 30.0 I 1 1 I I I


Minor or no MiteriaYEquipment Loss

Generally on time Materials Oeiivery

Poo r Design Quaiitg Major Design Changes 100 90 90 93.3

Presrnce of Scope Creep

Complew Design Canstmctabiliry

Majar Design Changes

M i r or n o MatenallEquiprnmt Loss

Generang on time Materiair Oekery

Mmor or no Matenal Waste

Frequent Projecc Material Shortage

Complcr Design Constructabiüty 1 1 1 1 1

Frequent Proiect Matenal Shorrage

Good Design Quafity

Preseme of Scope Creep

10

1

50

Maior Design Changes

3

10

4

5

Routine

2

10

40

Poor Design Quaiity

Presence of Scope Creep

Routine Design C4nstructabiIity

6

7

- -

Design Qualiry 1 h l l io r Design Changes

20

Poor Design Qualitg

No Scope Creep

Compler Design Constructabiiiq

Good Oesign Quality


Rautinr Oesign Constructabitity

Scope Creep I

3

50

13.3

60

I

Good Design Quality

N o Scope Creep

Cornplsx Design Consuuctabiiity

Poo r Design Qualitg

No Seope Creep

Routine Design Constnictabiiity

Oesian Constructabiitu 1

Used

vm

Major Design Changes

Maior Oengn Changes

Belief Nenrork haS.sis of Direct Cos! Risk in Building Constnrcrion 147

60

50 Major Design Changes

Maior Design Changes

Major Design Changes

53.3

90

/ 70

-

10

80

80

-

30 20 35.0 55

10

70

20

40

13.3

5-

Routine Design ConNuctabiTity 1 1 1

Valu

Use!

93.:

031

732

76-7

70.a

56.7

73.3

30.0

Adequate QuaGfÏed Local Labour

Poor Trade Coordination

Poor Oesign Quaiity

IO#

24 1

2

3

4

5

6

7

8

Belief Nehrork rimlysis of Direct Cost Risk in Building Conscnlcrton 148

Major Oefective Vork

Adequata Quaiified Local Labour

Good 'Frade Coordination

Poor Design Quaiity

Complen Design ConsuuctabiIitg

Cause

Insuffiuiciènt QuaGfied Local Labour

Poor Trade Coordmation

Poor Oesign Quaiitq

Compler Desfgn ConswctabiGty

Inniflicient QuaGfied Local Labour

Poor Trade Coordiination

Poor Design QuaGtg

Routine Oesign Connnictabiütjl

Insufficitnt QuaEfied Local Labour

Good Tnde Coordination

Poor Oesign QuaGq

Complcr Design Constnictabiüty

Insuffiàent Qualilied Local Labour

Poor Trade Coordinaiion

Good Design Quaiitg

Complea Design ConstmctabiGty

Adequate Qualified Local Labour


Poor Oesign Qualirp

Compler Design Consuuctabiity

Insufficient Qualificd Local Labour

Gaod Trrde Coordination

Poor Design Quaiity

Routine Design Conscnictability

Inniificient Pualified Local Labour

Poor Trade Coordiiation

Good Design Qualitjl

Routine Oesign Constructabiiity

Insufficient Qualiiicd Local Labour

Good Trrde Coordination

Good Design QuaGty

Complex Design Consuuctability

3

30

70

70

80

60

50

70

30

1

90

BO

70

00

80

70

70

40

Ufect

M m Defeuiwe Work

M J P Oefectiwe Wort

Maior Oefective Work

Major Defectiue Work

Major Oefective Work

Major Oefecrive Work

Maior Oefective Work

Major Defective Wotk

&put

2

100

100

80

70

70

50

80

20

60

Maior Oefective Woik

70

40

60 633

43.3 1

50 40

IO# I Cause

Qualified Local Labour

Trade Coordiiation

Good Design QuaGtg

Cornplex

12 Insufficient Quaiified Local Labour

1 Good r r h d r Coordination

~ o o d Design Quality

1 Routine Design Consuuctabüity I

Qualitied Local Labour

Trade Coordination

Oesign Qualicg

Routine Design Constructahility

Effect Enpert Value

1 2 3 Used

Major Oefecciue Votk 50 60 70 60.0

Major Oefectiue Wotk 60 20 40 40.0

Major Oefectiue Vork 50 20 20 30.0

I I I 14 1 Adequate QuaEfied Local Labour Major Oefective Work

Poor 1 Ciood

Trade Coordination

Design QuaIitg

1 Routine Design Constructability

I 15 Adequate Qualified Local Labour

T r d e Coordination

Design Quality

Compter Oesign Construcrabilicy

Maior Oefective Vork 1 10 10 7.0

I -

16 Adequate Qualified Local Labour

/ Good Trade Coordination

1 Good Design Quafity

1 Routine Desian Constniccabilitu

25 1 1 lnsufficient Qualified PM Personnel

Cornplex Design Const~ctabiïq

Large Phgsical Projecr Size

Routine Oesign tonstrucrability

3 Insufficient Qualified PM Personnel

Complex Design Consuuccabilicy

Srnall Phgsical Proiect Sire

+ Insufficient Qualified P M Personnel

Routine Design Con-iuctability

Srnall Phgsical Pioicct Size

5 Adequate Qualified P M Personnel

Complex Design Constructability

Large Phgsical Proiect Sire

Trade Coordination 11 Trade Coordiiation

'oor Trade Coordination

>oor Trade Coordination 50 80 70 66.7

%or Trade Coordination

Belief A'envork Anaipis of Direcf Cosr Ri& in Building Consrnrcrion 149

6

l 1

8 Adequate QualiiÏed PM Personnel Foor Trade Coordination

1 t

1 Routine Design Constructability I

Adequate QuaIified P M Personnel

Camplem Uesign Constructability

Small Physical Project Size

26 t Very Sensitive Physical Environment Maior Regulatory Penalties

1 I


Poor Trade Coordination 7 Adequate Quafilied P M Personnel

Routine Design Constructability

Large Phgsical Proiect Size

2 1 Moderately Sensitive Physieal Environment 1 Milaior Regulatory Penalties 1 60 ( 30 1 50 1 46.7

I I I I

1

40

50

27 1 1 lnsulficient Local Suitable Materials 1 Frequently late Materials OeIivery 1 1 I 1 I 1

28 1 1 Reaciive Proiect Manager CooperativeEnuironment 1 80 1 80 1 80 1 80.0 1

2

IO

10

3

30

30

Insufficient Qualified P M Personnel

Used

26.7

30.0

1 1 1

2

4 I~ roac t i ue Project Manager Cooperative Environment 1 20 1 1 1 30 1 17.0 1

I

29 1 1 Worse than Enpected &change Rates 1 >erpected InternationalMarketPrices 1 90 [ 100 1 100 1 96.7 1

Reactive Proiect Manager

Adequate Qualified P M Personnel

1 I

No Cooperative Environment 3

t Proactive Proiect Manager

Insulficient Qualified P M Personnel

Proiect uses Foreign Purchased Goods

3 1 Worse than Eupected Enchange Rares International Market Prices 1 - IF-1 1.0 1

Na Cooperarive Environment

40

1 1 2

50 50

4 1 As ewpected or bctter &change Rates InternationalMarket Prices 1 IO 1 l 1 1 1 4.0 1

40

I As çupected or better Enchange Rates

Proiect uses Foreign Purchased Goods

Proiect does not use Foreign Purchased Goads 1 1

- -

Exchange Rates Foreign Purchascd Guods 1 80 1 80 1 70 76.7 1

70

I

1

Suitablc Equipment 1 1 1 1 1 1

56.7

40

>ewpected International Market Prices

1

Belief ~Venvork Anaiysis of Direct Cost Risk in Building Consrnrcrion 150

40.0

10 IO 10 10.0

cause

I

2 As expected or better Enchange Rates Ptoiect uses Foreign Purchased Goods

1 Adequate Suitable Equipment 1 I I I

3 Worse than Eiipected Exchrnge Rates Project uses Foreign Purchased Goods

1 Adeqwte Suitable Equipment 1 I I I

4 A s ewprcted or better Exchange Rates Roject uses Foreign PurchasPd Goods

31 1 [Construction Saturated Local construction rnarkec 1 tnsuffiaent Local Suitable Materials

I I 2 Normal Local construction market Insuffiuent Local Suitabte Materials

32 1 Insufficient Suitabk Equiprnent cewpected Equipment Productivity

Worse than Enpected Ground Conditions

High (>3000ft] Altitude

I I 2 Insufficient Suitable Equipment texpecled Equipment Productivity

1 Worse than Enpected Ground Conditions 1 1 Normal Altitude 1 I I

3 Insufficient Suitable Equipment c expected Equipment Productivity

As erpected or better Ground Conditions


+ Insufficient Suitable Equipment

A s eipected or better Ground Conditions

texpected Equipment Productivity

1 Normal Altitude 1 I I

5 Adequate Suitable Equipment texpected Equipment Productivity

Worse than Enpected Ground Conditions


6 Adequate Suitable Equipment ccxpected Equipment Productivity

Vorse than Ewpected Ground Conditions

Normal Altitude

7 [ ~ d e q u a t r Suitable Equipment 1 <erpected Equipment Productivity

1 A s etrpecced or better Ground Conditions I 1 High [>3000ft] Altitude 1 1 I I

0 Adequate Suitable Equipment texpected Equipment Productiuity

16s ewpccted or better Ground Conditions I Altitude 1

33 1 1 Construction Srturated Local canstruction market 1 1nsufficier:t Suitable Equipment

Expert Value

Belief Nenvork Analysis of Direct Cost Risk in Building Construction 151

: I ~ e m o t e Project Geagraphy

Normal Local construction market

Major MateriatlEquipment Loss

Remote Proiect Geography

Construction Poor Local canstruction market 1 Maior MaterialfEaui~ment Loss

ld f i c ien t Suitable Equipment 70

I Insufficient Suitable Equiprnwt 50

Rural Project Geography Insuflicient Suitable Equipment 50


Maior MateriallEquipment Loss

Rural Project Geographg Insuffitient Suitable Equipment 25


Minar or no MaterialfEquipment Loss

Urban Project Geogrophy Insufficient Suitable Equipment 40


Major MateriaIf Equipment Loss

1

Urban Project Geography

1 Normal Local construction market

1 ~ n o r or no MateriallEquiprnent Loss

I

Insufficient Suitable Equipment 10

8 1 Rural Project Geography 1 lnsufficient Suitable Equipment

( Construction Poor Local construction market 1 1 Maior MaterialfEquipment Loss 1 1 I I 1 1 I

9 Rural Project Geographq Insufficient Suit able Equipment 1 O

Construction Poor Local construction market

Minor or no MaterialiEquipment Loss

10 Urban Project Geography lnsufficient Suttable Equipment 40


Major MateriallEquiprnent Loss

1 I

11 Urban Project Geography Insuffiment Suitable Equipment 1 O

1 Construction Poor Local construction market 1 I 1 Minor or no MateriallEauioment Loss 1 !

34 1 1 Atypical Site Sccurity

I 1 Major MateriallEquipment Loss -

35 1 1 Construction Saturated Locd construction market 1 lnsufficient Qualified Local Labour

I I 2 ( Normal Local construction market Insufficien t Qualified Local Labour 20

1

3 1 Construction Poor Local conuruction market 1 Insufficient Pualified Local Labour 1 60

BelieJ'Nenvork Anaiysis of Direct Cost Risk in Building Constnrcrion 152

Value

36 1 ünfavourable Geology

2 Favourable Geology

No Archaeohgical Swey

3 Unfavourable Geology

Perforrned Archaeological Suwey

I

4 Favourable Geology

37 1 Poar Design Tearn Coordination

Presence of Sape Creep

2 1 POO^ Design Tearn Coordination

1 NO Scope Creep

I 1

3 Good Design Tram Coordination

1 Presence of Smpe Creep

I I

4 Gcod Design Team Coordination

38 1 l ~ n ~ r o v e n Construction Tech. Required

Poor Design Tearn Coordination

Presence OF Scupe Cresp

~ - ~ --

2 Prooen Construction Tech Required

Poor Design Tearn Coordination

Prescnce of Scope Cieep

3 1 Unproven Construction Tech. Required

1 ~ o o r Design Team Coordination

1 NO Scope Creep

I Construction Tech. Required

Design Team Coordination

Prescnce OF Scope Crecp

5 Proven Connruction Tech Required

Poor Design Team Coordination

No Scope Crecp

6 Proven Construction TechRequired

Good Design Tcarn Cocrdinaticn


1 2 3

Worse than ewpected Ground Conditions 90 80 60

Worse than expected Ground Conditions 20 50 50

--

Vorsr than expccted Ground Conditions

1 I

Worse than expected Graund Conditions 10 20 20

Late Design Submittal

Late Design Submittal 80 80 80

I

~ a t e Design Subrnittal 60 40 80

Late Design Subrnittal

Poor Oesign Quality

Poor Oesign Qualicy

Poor Design Quality 70 80 80

Poor - -

Design Quality

=oor Design Quality 50 70 90

JO of Design Puality

Belief AknvorX- Analysis of Direct Cosf Risk in Building Construction 153

0 Proven I -- Construction Tech. Requued Poor

D M g n Team Coordination

ID#

7

Oesign Quality

Effect

Poor Design QuaTi

Cause

Unproven Connrueiion Tech. Re-d

Good Design Tearn Coord;nation

No Scope Crop

Tmant Requnernent Change Presence of I Scope Creep

Oesian Team Coord

39 1

2

Minor Tenant Requirernent Change 1 Presence o f Scope Creep

Value

Used

26.7

Expert

Good Design Tearn Caord. 1 1 1 I

1

30

Major Tenant Requüernent Change

Poor Design Team Coord

Major Tenant Requuernent Change

Gond Design Team Caord

I I f N o Tenant Requirernent Change Scope Creep 1 25 1 40 1 65 Igf Poor Design Team Coord. 1 1 1 1 I

2

40


Presence o f Scope Creep

Tenant Requirernent Change Presence o f I Scope Creep

Dcsian Team Coord

3

10

40 1 1 Fmancially Unstable Owner 1 Forbidden Budget revisions

100

Insufficient Qualified PM Personnel Reactive Project Manager 80 80 70 76.7

lnewperienced PM work familiarity 1

90

3 1 Adrquate Qualificd P M Personnel 1 fleactiue Prolecl Manager 1 60 1 60 1 20

2

1 lnenperienced PM work familiarity 1 1 1 1 l

100

100

90

1 1 f

4 Adequare Qualified P M Personnel Project Manager

96-7

60

Insufficient Qualified P M Personnel

Enperienced P M work familiaritg

42 1 l ~ u m p m m Contractor Payrnent Type 1 R i k t o contractors by Conuact Clauses

I l I - -

2 1 unit ric ce Contractor Payment Type 1 Risk tu contractors by Cantract Clauses

I I l 1

Aeactive Proiect Manager

--- -- ---

3 1 Guaranteed Maximum Contractor Payrnent Type 1 Risk to contractors by Contract Clauses 1 90 1 70 1 70 1 76.7 I I I I I

4 1 Cost reimbursable Contractor Payment Type 1 Risk to contractors by Contract Clauses I 1 0 l 1 1 1 1 4 . 0

50

Belief Nencork Analysis of Direcr Cosr Risk in Building Consrnrc~ion 154

40.0 40 30

Cause Eifect

5 Lumpsum Contractor Payment Type Risk t o owners bg Contrau CIauses

6 Unit Price Contractor Pagment Type Füsk t o owners by Contract Clauses

Aak t o owners by Contract Clauses 7 1 Guaranteed Maximum Cantractor Payment Type I

43 1 1 Unproven Construction Tech. Requïred 1 lnesperienced PM work familiarity

I I

Qualified P M Personnel 1 P o o r P M knowfedge o f area

I I

I I I

45 1 insufficient Qualified P M Personnel Maior ConstructiodOps Interference

Other Cornpeting activity o n site

Interfering Traffic Congestion

I I

2 l ~ d e q u a t e auafified PM Personnel 1 Major ConstnictionfOps Interference

Oc@ - . - - . Cornpeting - - activity -. o n site

lntcrfering Traffic Cangcstion

f 1 1

3 Insufficient Quafified P M Personnel Maiot ConstructionlOps Incerfetence

1 Other Competing activity o n site 1 1 NO Incethring Traffic Congestion 1 I

4 1 Adcquate Qualified PM Personnel Major ConstructionlOps lnterference

1 Othcr Competing accivity on site 1 1 NO Inteiferïng Traffic Congestion 1 I

5 Insutficienc Qualified PM Personnel Major C o ~ t r u c l i o n l O p r Interference

1 N o Ochrr Cornpeting activity on site 1 Interfering Traffic Congestion

I Major ConstructionlOps Interference

-

6 -

Adequate Qualified PM P e r s o ~ e l

Na Other Competing actiuity on site

lntrrfering Traific Congestion

Major ConstructioniOps Interference 7

Quafificd P M Personnel ConstructionlOps Interference

tnsufficient QuafiRed P M Personnel

N o Other Cornpeting activity o n site

N o Interlering Traffic Congestion

Behef Nenvork Analysis of Direct Cos! Risk in Building Consrrucrion 155

I value Cause I Effcct

46 t

2

3

+

Interfcring Traflic Congestion

Small Physïcal Proiecc Size Interfering Traffc Congestion

Olher Competing activiry on site

Srnall Physical Proiect Size Interferhg Traffic Cangestion

No Carnpe!ing activiq on site

Large (for projectsize] Number of Workers on site

Adequate Site accesslegress lnterfering Traffic Congestion

Large [for proiecc sire) Number of Workers on site

Other Competing Activity on site

Large Physical Pro jut Sire

Insufficient %te accesslegress Interfering Traffic Congestion

Large [for project site] Number of Workers on site


Large Physical Proiecc Size

5

6 Interfering Traffic Congestion

Insufficient Site accerslegress

Small [for proicct size] Number of Workers an site


Large Physical Proiect Sire

Adequate Çite accesslegress

Smalt [for proiect size] Number of Workers on site


Large Physical Project Size

lnsuf ficient Site accesslegress Interfering Traffic Cangestion

Small [for project sire] Number of Workers on site

No other Compcring Activity on site

Small Physical Project Size

- - -- - --

Adequate Site accesslegress lnterfering Traffic Congestion

Small [for project sae] Number of Workers on site

No other Cornpeting Activity on site

Small Physical Proiecc Size

Insufficient Site access/egress lnterfering Traffic Congestion

Large [for proiect size] Number of Workers on site

No othcr Competing Activity on site

Large Physical Project Sire

Interfering Traffic Congestion 10

Belief Nenvork Anaiysis of Direct Cos[ Risk in Building Constnrction 156

Adequate Site accessiegress

Large [for proiect sire) Nurnber of Vorkers on site

No other Competing Activity on site

Large Physical Proiect Sire

IO# Cause Effect I . Expert Value

1 11 InnilFiaent Site accesslegess Interfering Traffic Congestion

S m l l [for proiea ske] Numher of Vorkers on site

Adequate Site accesstegress Interfering

Srnall [for proiect size] Nurnber of Vorkers on site

No other Competing Actiuity on site

Larae Phusicat Praiect Size

-

Traffic Cangestion

( Ptesrnce of. [location knawn] Utilitics 1 ~eue re Perrnits Required 1 30 1 50 1 50 1 433 I I I I t I

Cornplen Design ConstnicwbTty 1 Unproven Construction TechRequired 1 90 1 80 1 70 1 80.0

I I I I I

Presence o f (location unknown] Utiiities

Qualified PM Personnel 1 Pour Design Teun coordination 1 90 1 90 1 90 1 90.0 I 1 I I I I

50 1 1 Construction Saturated Local construction market 1 lnsulficient Qualified PM Personnel 1 80 1 90 1 80 1 ô3.3 I I I l l t

Severe Pcrmits Required

- - -- -

2 1 Normal Local consvuction market Insufficient Qualified P M Personnel 30 30 40 1 33.3

90

1 Non-Prosperous

51 1

Area affluence

80

-- -

Auailable Support Faciiities ( 50 1 46.7 1

Non-Prosperous Area affluence

Construction Saturated Local ccnstruction market

50 &%$

Insufficient Available Support Facitities

Normal Local construction market 1 1

Non-Prosperous Area affluence

Consrruction Poor Local construction market

5 1 Prosperous

70

I I I I

Prosperous Arca affluence

Construction Saturated Local consuuction market

Area affluence

Insufficient Auailable Support Faciiities

--- 1 lnsufficient Available Suppart Ficilitier 171 1 50 1 46.7 1

50

Insufficient Available Support Facilities

1 Normal Local construction market 1 1 1 1

40

60

Belref Nenvork rlnalysis of Direct Cosr Risk in BuiMing Consrniciion 157

60.0

30

53.3 ! I

6

40

50 60

Prosperous Area affluence

36.7

50

M f i c i e n t Available Support FacJitier 20 40 40 33.3

--

ff fect Value

Used - 46.7

ln* I Cause

52 1 l>usual Gov. Construction Spendng Private Funding Source

1 Unstable Government

1 2 >usual Gov. Construction Spending

Stable Governmenc

Private Funding Source

Private Funding Source 3 1 AS usual or lower Gov. Construction Spcnding

1 Unstable Government I

4 As usual or lover Gov. Construction Spcnding

Stable Governrnenc

Private Funding Source

5 (,usual Gov. Conrrruction Spending Public Funding Source

1 Unstable Gouernrnenc I

6 >usual Gov. Construction Spending

Stable Government

Public Funding Source

1

7 As usual or louer Gov. Construction Spending Public Funding Source

1 Umtabie Government 1 I

8 As usual or lover Gov. Construction Spending Public Funding Source

1 Stiblr Gouernrnent

> expected Construction Market Escalation Inflation

Gov. Construction Spending

1 Construction Saturated Local construction market

> ewpected Construction Market Escalation 1

2 As usual or lover Inflation

1 > usual Gov. Construction Spending

1 Construction Saturated Local construction market

3 >usual Inflation > erpected - - -

Construction Market Escalacion

1 AS usual or lover Gov. Construction Spending

1 Construction Saturatcd Local construction market

I > erpected Construction Market Escalation 4 As usual or lover Inflarion

As usual or louer Gov. Construction Sprnding

Construction Saturated Local construction market

> erpected Construction Market Escalation 5

6 >ewpected Construction Market Escaladon

>usual Inflation

> usual Gav. Construction Spending

Normai Local construction market

As usual or louer Inflation

> usual Gov. Construction Spending


Belief Network Anafysis of Direct Cost Risk in Building Consrmcrion 158

Effcct

1 Z 3 Used

7 >usual Inflation > ewpected Conmucrion Market Escalation 80 ?O 40 2& r7

As usual or low-r Gov. Construction Spendmg

Normal Local conmuction market

B A s m a l or louer Inflation >erpected Construction Market Escalation 10 20 10 13.3

As usual or lover Gov. Construction Sprnding


> usual lnfbcian > ewpected Construction Market Escalation

>wual Gov. Construction Spending


As wual or lower

r usual

1 >ewpected Const~ction Market Escalacion

Gov. Construction Spending 1 Construction Poor Local construction market 1

I , usual Inflation ,expected Constwction Market Gcatation

As usual or lover Gov. Construction Spending


As usual or lower Inflation >eupected Construction Market Escalacion

As usualor louer Gov. Construction Spending

nstruction Poor Local mmtnicuon market

54 1 Remote Proiect Geography lnsufficient Availability of Energy BO 70 70 73.3

1 1 1 I -- -- -

2 1 Rural Project Geography 1 lnsufficient Availabiiity of Energy 50 50 50 50.0 1 I 1 I I I

55 1 1 >usual Gov. Construction Spending 1 >erpected Inflation

56 1 IUnstable ûovernment Gov.Construction Spending 1 60 30 40 ( 43.3

5ï 1 Unstable Government > erpected Tan Rates 1 50 1 40 1 30 1 40.0 I 1 I I 1 1

2 1 Stable Government 1 > exnected Tan Rates 1 50 1 30 1 20 1 33.3

58 1 1 Unfavourable Geology 1 Likely Land-relatedNaturalOiaster 1 - 1 30 1 30 f 30.0

1 1 1 I I I 1 I l 1 1

2 Fauourable Geology Likely Land-relatedNaturalOisaster 1 10 1 10 / 30 16.7

20 responses that did not make sens+ wert eliminated from che data set- They were climinatcd bccause enamination of the

possible state combinations. and their relative scores did not make sensa

Each of the rcsponscs that vcrc eliminatrd. the ewpcrts wrre consulted and asked if thty obietttd to the

value that was bdng usrd in the model. No obections were made.

36 mode1 values were alterrd in such a way that they accomodated al1 of the expert rcsponses.

Belief Xehrork Anaiysis of Direct Cos! Risk in Building Consmrc~ion 159

Prior Probabilities Required

1 . . , . - Contractor Failure

2

4 a Lona Work Stoaaaaes


3

5 Labour Iniuries/Accidents I

Sumlier Failure - - - -

7 Tenant Reauirement Chanae

6

i3 Contractor Pavment Tvoe I

Archaealogical Survev

9'site Securitv

10 Site Access

11 Nurnber of Workers on Site I 12 Ecolaaicâl Environment i 14 Local Construction Market I

State 1 Probability (1-100) 1 Contractor Fails No Contractor Fails

0.30% 99.70%

Subcontractor Fails No Subcontractor Fails

1% 99Oh

Supplier Fails NO Supplier Fails

1% 99%

Major Construction Stoppages Minor or No Construction Stoppages

30 % 70 %

Major Injuries Occur Minor or no Injuries Occur

Major 20% Minor 60% None 20%

10% 90%

Archaeological S u ~ e y Performed No Archaeological Suwey Performed

Lump Sum Unit Price Guaranteed Maximum Cost Reimbursabie

50% 50%

Typicat 80% A t v ~ i c a l 20%

Large (for project size) Small (for project size)

Not verv sensitive 1 20% 1

50 % 50%

Very Sensitive Moderately Sensitive

Saturated I 20% I

20% 60 %

Belief Xenvork Analysis O/ Direct Cosr Risk in Building Consrnrcriott 160

Normal Poor

60% 20%

Prior Probabilities Reguired

Variable . . - - . - - . . -. , Probability (1-100) State

Owner

Phvsical Proiect Size Large 90% Srnall 10%

Comaetina Activiiv on Site - -

Utilities

Othe? activjty competing No other activity competing

Not present

50% 50%

Present , location known Present . location unknown

L

15%

Area Affluence

60% 5%

Exchanqe Rates

1

Prosperous Not prosperous

Government

85% 15%

Worse than expected A s expected or better

Weathar Extremes

AItitude High (>300Q ft) 5% Low (~3000 ft) 95%

50% 50%

Stable Unstable

Geoloay Favourable 70% Unfavoura ble 30 %

95% 5%

Likely Unlikely

90% 10%

60% 30%

Climate

Beltef ~Venvork Anaiysis of Direcf Cos[ RI& in Building Consfnic[ion 161

5% 95%

Moderate Extreme

Geoaraahy Urban Rural

Appendix J: Divorcing Variable Ranking

Belief Xenvork Anaipis of Direct Cost R~sk in Building Constmction 162

Desinn Claims: Ranking

Changes Creep Major 1 Minor Mejor 1 Minor

PM Claims Mitigation: Ranking

- - - - - - -

Delay Clairns: Ranking

1 Dela y s 1 Overtime 1

1 2

3

4 5 6

7 8

Belief Nenvork Analysis of Direcr Cosr Risk in Binlding Consrnlcrion 163

1 2

3 4

Delays Major

X

X X

X

Major

X

X

Mirtar

X

X X

X

Overtime

Major

X

X X X

Stoppages

Minor

X

X

Minor

X

X X

X

Major

X

X

X X

Minor

X X

X

X

Major

X

X

Minor

X

X

Feilure Detays: Ranking I I Contredor 1 Subcontractor f Supplier I

Labour Delays: Ranking I

Major

Praductivity Defective Stoppages Coordinatian Major Minor Major Minor Major Minor Mejor Minor

X X X X X X X X

X X X X X X X X X X X X


X X X X X X X X


Logistics Del-: Ranking

1 Deliverv 1 lnterference

Minor

X

Design Delays: Ranking I

Major

1

Changes Submitial

Major Minor Major Minor 1 2 3

Belief Nenvork Anaiysis of Direct Cosr Risk in Brrilding Consmrclion 164

Minor

X

Major

Mejor

Minor

X

Minor

X

Major Minor

X

Conditions

1

Geolagy Disaster

Major 1 Minor Major 1 Minar

Short Breaks: Rankina

Bclief ~Venvork Analysis of Direct Cost Rlsk in Building Consrrucrion 165

Avaitebiiiiy

Major Minor

X

X

Injuries

Major

Climete

Minor

X

X

Major

X

Minor

X

Labout Congestion: Rankirtg

Workers Congestion Interference

Mejor Minor Major Minor Mejor Minor

X X X X X X

3our DesTon Understandino: Rankino

Belie f Nehvork Anaiysis of Direct Cos1 Ris& in Blnlding Consrnrcrion 166

Technalogy

Major

X

Minor

X

X X

Chenges Lebour

Major Mejor

X

Minor

X

X X X

Minor

X

X X

Appendix K: Data Reduction Description

Belief Yencork Analysis of Direct Cosr Risk in Building Consrrucrion 167

Relationship Elimination: Design Claims

Original Design Claims Parents: Design Changes Change in Tenant Requirements Design Quality Scope Creep Design Tearn Coordination Complexity/Constructability of Design

Scope Creep Change in Tenant Requirements Design Team Coordination

Design Timeliness Design Tearn Coordination Scope Creep

Change in Tenant Requirements NO PARENTS

Relationship Elimination: Eliminate conneetion bebveen "Change in Tenant Requirements" and "Design Claims"

Justification: "Change in Tenant Requirements" already affects "Design Claims" through "Scope Creep" and "Design Changes"

Revised Design Claims Parents: Design Changes Scope Creep Design Timeliness

Belief Nenvork ..lnalysis of Direct Cost Risk in Building Constntction 168

Relationship Elimination: Labour Deiays

Onginai Labour Delays Parents: Labour Productivity Short Breaks Defective Work Labour Congestion Labour understanding of design

Qualified Local Labour Local Construction Market Saturation

Defective Work QuaIified Local Labour Trade Coordination Design Quality Complexity/Constructability of Design

Long Work Stoppages PARENTONLY

Trade Coordination Available qualified key PM personnel Complexity/Constmctability of Design Physical Project Size

ReIationship Elimination: Elirninate connection between "Qualified Local Labour7' and "Labour Delays"

Justification: "Qualified Local Labour'' affects "Labour Delays" through "Labour Productivity" and "Defective Work"

Revised Design CIaims Parents: Labour Productivity Defective Work Long Work Stoppages Trade Coordination

Belief Nenvork Anuiysis of Direcr Cosr Risk in Buctding Consrrucrion 169

Relationship Elimination: Project Material Shortage

Original Material S hortage Parents: Local Suitable Materials Local Construction Market Saturation

Design Changes Change in Tenant Requirements Design Quality Scope Creep Design Tearn Coordination Cornplexity of Design

MateriaVEquipment Loss/Darnage Site Security

Materials Delivery Promptness Local Suitable Materials

Material Waste Defective Work

Relationship Elimination: Eliminate connection between "Local Suitable Materiais" and "Project Material Shortage"

Justification: "Local Suitable Materials" affects "Project Material Shortage" through "Materials Delivery Promptness"

Revised Project Material Shortage Parents: Design Changes MaterialiEquipment Lo ss/D arnage Materials Delivery Material Waste

Belief iVenvork Rnalysis of Direct Cost Risk in Building Construction 170

ReIationship Elimination: Design Changes

Original Design Changes Parents: Change in Tenant Requirements PARENTONLY

Design Quality Construction Technology Requirements Design Tearn Coordination Scope Creep

Scope Creep Change in Tenant Requirements Design Team Coordination

Design Team Coordination AvailabIe key PM personnel

Complexity/Constructability of Design PARENTONLY

Relationship Elimination:

Justification:

Elirninate connection between "Change in Tenant Requirements" and "Design Changes" Eliminate connection between "Design Team Coordination" and "Design Changes"

"Change in Tenant Requirements" affects "Design Changes" through "Scope Creep" "Design Team Coordinationy' affects "Design Changes" through "Scope Creep" and "Design Quality"

Revised Design Changes Parents: Design Quality Scope Creep Complexity/Constructability of Design

Belief Nenvork Anaiysis of Direct Cos! Risk in Building Constrtrcrion 171

Appendix L: MSBN Text File

BeIief'~Vencork rlmlysis of Direct Cost Risk in Building Constnrctiot~ 172

diagnostic nehvork "" node Equiprnent

name: "Cost of Equipmrnt"; type: discrete[81= 1

" L 15%". "95%". "75%". "55%". "35%". " 13%". "- "-25%"

1: position: ( 12093, 18985): label: informational; cost: observe = 1.00;

I

nodeLabour

narne: "Cost of Labour"; type: discrete[8] = (

"1 15%". "95%". "75%", "55%". "35%". " 15%". "- jO/o"7

"-2 j%"

1: position: ( 16857, 19000): IabeI: informational; cost: observe = 1.00;

I

node Material {

narne: "Cost of Materials"; type: discrete[8] = {

" 1 15%". "95%", "75%". " 5 5 % , "3 5%". ', 15%". "-5%" "-2 5%"

1 - 1 r

position: (22050. 19000): label: informational: cost: observe = 1.00:

1

{ name: "Consuuction Clairns"; type: discrete[2] =

"Major". "Minor or no"

j: position: (15505, 14335);

1

Belief Nenvork Analysis ojDirecr Cosr Risk in Building Consfnrction 173

{ name: "Design Claims"; type: discretel21 =

"Major", "Minor or no"

1; position: ( 19675. 14335):

1

node FieldClaims {

name: "Field Claims": type: discrete[2] = {


1: position: (1 7200, 14333):

1

node DehyClaims I

name: "Delay Claims"; type: discrete[2] = {


1; position: (18385. 14335):

1

node PMClaimsMitigation

name: "PM daims mirigation": Qpe: discretel21 =

{ "PM effective". "PM Ineffectivs"

1: position: ( 12220, 14335):

1

node ContractClauses {

name: "Contract Clauses"; type: discrete[3] =

"Risk to conuacton", "Risk to owner", "Risk shared"

1; position: (13945, 14335);

1

node CntrcuPymntTyp

name: "Contractor Paymcnt Type"; type: discretel41 =

"Lump sum", "Unit pricc", "Guaranteed Mauirnum", "Cost reimbursable"

1; position: (IO 165, 13350);

1

node Ovenime {

Belief ~Venvork Anahsis of Direct Cost Risk in Building Cons[nrcrion 174

name: "Ovenime": type: discrete[S] = {

"More than e..pectedl', "& expected or las"

1; position: (24070. 10675);

1

name: "Construction Delays": type: discrete[2] = I


I : position: (23305. 121 00):

}

node FailureDelays

name: "Failure Delays"; type: discrete[2] = I


1: position: (22765. 10675):

1

node ContractorFailure 1

narne: "Contractor Failure": type: discrete[2] =

{ "Conuactor Fails", "No contractor fails"

1; position: (2 1220, 1 1500):

1

node SbcntrcuFIr

name: "Subcontractor FaiIure": type: discrete[2] =

"Subcontractor fails". "No subcontractor fails"

1: position: (19380, 1 1435):

1

node SupplierFaifure {

name: "Supplier Failure": type: discrete[2] = (

"Supplier Failsn, "No supplier fails"

I - 1 r

position: ( 1 7995, 1 1470); 1

node LabourDelays I

name: "Labour Delays"; type: discrete(21 = {

"Major".

Be fref A'envork rlnalyss oj' Direct COSI Risk in B~rilding Construction 175

1; position: (10 [Os, 11455);

node LogisticsDelays {

name: "Logistics Delays"; type: discrete[2] = C

"Major". "Minor"

1: position: ( 1 1875. 12130);

}

node DesignDelays

name: "Design Delays"; type: discrete[2] = I

"Major". "Minor"

1; position: (13300, 12145);

I

node EnvironrnentalDelays {

narne: "Environmental Delays": type: discrete[2] = {

"Major". "Minor"

1; position: (16225, 12145):

node LandDelays f

name: "Land Delays"; type: discretel21 =


1; position: (20290. 12130);

1

node LabourProductivity I

nanie: "Labour Productivity": type: discrete[2] =

C "Less than expected", "AS expected o r better"

1; position: (10105, 10720);

1

node ShortBreaks (

narne: "Short Breaks": type: discrete['] =

{ "Frequent". "Infrequent"

1; position: (1 1845, 10705);

1

Belief Nenvork -4naiysis of Direcf Cosf Risk in Building Consfntction 176

node LabourCongestion

name: "Labour Congestion": m e : discrete[2] = t

"Interference". "No Interference"

): position: (21 160' 10675):

node LbrDsgnUndnrndng I

name: "Labour Design Understanding": type: discrete[2] = {

"Good", "Poor"

1 position: (22750, 1 1500);

I

node WrkQnttyDvtns

name: "Work Quantity Deviations": type: discret@] = {


node MaterialShortage

name: "Marerial Shortage": type: discret@] = {

"Frequently inadequate". "Infrequently inadequate"

i ; position: (21625, 121 15):

}

node MaterialWaste {

name: "Material Waste": type: discrete[2] = I


1; position: (13 133, 10705);

1

node DefectivrWork I

name: "Defective Work": type: discrete[2] =

{ "Major", "Minor or no"

1 : position: ( 13770. 12 1 15);

1

nodc EqpmntPrdctvty i'

name: "Equipment Productivity";

BeliejiVenrorA- Anaiysis of Direct Cosr Hisk in Building Constnrction 177

type: discrete[2] = {

" L e s than expected". "As expected or better"

1; position: (10060. 12145);

1

node MtrlEqprnntLss {

name: "MateriaVEquipment Loss"; type: discrete[2] =

{ "Major". "Minor or no"

I - > r

position: (13585. 1 1425);

node LbrInjrsAccdnts {

name: "Labour Injuries/Accidentsl': type: discrete[2] = {


I : position: (18 145. 12145):

1

node ArchlgclSrvy I

narne: "Archaeological Survey"; type: discrete[2] =

t "Performed", "Not performrd"

1: position: (1 1590, 1 1425):

I

node CnstrcmOprtnsIntrfrnc

name: "Consuuction/Opentions Interference"; type: discrete[2] = {


I . 1 7

position: (22255. 12835); 1

node TraficCongestion {

name: "Traftïc Congestion"; type: discrete[2] =


1: posirion: (1 35 15, 10705);

}

node NmbrOfWrkrsOnSt

narne: "Number of Workers on Site": type: discrete[2] = {

"congested", "Non congested"

Belief Nenvork A n a t ' y of Direct Cost Rtsk in Building Constnrcrion 178

1; position: (16150. 10690):

nodr CnstrctnTchn IgRqmnts (

name: "Construction Technotogy Requirements"; type: discretc[2] = {

"Unproven". "Proven"

1: position: (1 82%. 10690):

1

nodr CostAccounting {

name: "Cost Accounting"; type: discrcre[2] =

{ "Timely", "Untirnely"

1; position: (1 1980. 169 15):

1

nodr TndeCoordination t

name: "Tnde Coordination"; type: discrctef2] =

"Good", "Poor"

1 i position: (21685, 16930);

I

narne: "Long Work Stoppages": type: discrete[7] = i


1: position: (10075, 16930):

1

node MaterialsDelivery

narne: "Materials Delivery"; type: discrete[2] = {

"Generally on tirne". "Frequently Late"

1; position: (20080, 16930);

1

node CprtvEnvrnrnnt f

name: "Coopentive Environment"; type: discretel21 = :

"Partnering practiced". "Partnering not practiced"

1; position: ( 15743, 16930);

1

Belief ~Venvork Analysis of Direct Cos! RÏsk in Building Conslnicfion 179

nodr PM l

1

name: "PM"; type: discrete[2] =

" Proactive". " Reactive"

1; position: ( 13465. 169 15):

node PMWorkFamiliarïty 1

name: "PM Work Farniliarity": type: discrete[2] = {

"Good". "Poor"

); position: (14080, 16930);

node PMKnowledgeO fArea 1

namç: "PM Knowledge of Area": type: discrete[2] =

"Good", "Poor"

1: position: (23305. 16930):

;

node Ql fdKyPMPrsnnl

namc: "Qualified key PM Personnel"; type: discrete[2] = {

"Adequaten. "Inadequare"

1: position: (17860, 16930);

1

node VafueEngineering t

namr: "Value Engineering": type: discrete[21=

"Not Practiscd". "Pnctised"

); position: (15100, 13570):

1

node DesignChanges {

name: "Design Changes": type: discrete[2] = {


1: position: (13015, 12790);

I

node DesignSubrnittal

narne: "Design Subrninal": type: discrete[2] =

Belief Kenrork Analysis of Direct Cos[ Risk in Bttilding Constnrcrton 180

I "Generally on tirne", "Frequently Late"

1; position: (101 65, 12790);

I

name: "Design Quality"; type: discrete[2] =

"High". " Low"

I; position: ( 16795, 13555):

I

name: "Scope Creep"; type: discrete[Z] =

"Presence of', "Absence of'

1: position: (1 1680, 12790):

}

name: "Tenant Requirement Change"; type: discrete[3] = I

"Majorn, "Minor", "No"

1: posirion: ( 12655, 13570):

1

node Cmplx&C~trctbIs.OfDsgn {

name: "Complexity/Constn!ciabil~ of Design": type: discrete[2] = {

"Cornples", "Routine"

1: position: (18 190, 13555);

1

node DsgnTmCrdntn !

name: ''Design Team Coordination": type: discretef21 = {

"Good", "Poor"

): position: (10 180, 13570);

1

node RegulatoryPenalties I

name: "Regulatory Penalties": type: discrete[î] = {


Belief ~Venvork Analysis of DÏrecf Cost Risk in Building Consrnrcrion 181

1 position: (14530. 12803;

1

node PemitsRequired {

name: "Permits Required"; type: discretet21 =

{ "Cornplex", "Normal"

1; position: (16375. 12805):

node GvmmnrSpndngOnCnstrctn (

name: "Govemrnent Spending on Constniction"; type: discrete[2] =

"Higher than usual". "As usual or lower"

1 i position: (17995, 12835);

1

node Govemment {

name: "Government"; type: discrete[î] =

I "Stable". "UnstabIe"

1; position: (20920. 12820):

1

node IntrntnlMrktPrcs {

name: "International Market Pnces": type: discrete[2] =

"Higher than espected". "As espected or lower"

1 : position: (20965, 13570):

node CnstrctnMrktEscltn {

name: "Construction Market Escalation"; type: discrete[î] =

( "Higher than expected", "As espected or lower"

1; position: (2 1070, 13320);

1

node inflation {

nme: "Inflation": type: discrete[2] =

I "Higher than r'cpected". "As expected or lower"

}: position: (23 155. 13570);

}

Belief Nenvork Anaiysis of Direct Cosr Risk in Birilding Construcrion 182

node TavRates {

name: "Ta-Y Rates"; type: discrete[2] =

"Higher thm in~pected", "As expected or lower"

I ; position: (24025. 13555);

t

node ExhangeRates {

narne: "Exchange Rates"; type: discretel21 =

{ "Worse than Expected". "As expected or better"

1: position: (23500. 14290):

1

node FrgnPrchsdGds {

name: "Foreign Purchased Goods"; type: discrete[2] =

{ "Used", "Not used"

1 i position: (2 1415, 16105);

}

node LclStblMuls

name: "Local Suitable Materiais": type: discrete[2] = {

"Adequate", "Inadequate"

1; position: (14650, 16 105);

1

node Stbl EqpmntAvlblty

name: "Suitable Equipment AvailabiIity": type: discrete[î] =

"Inadequate", "Adequate"

1: position: (10 165, 16 120);

node QlfdLcILbr

name: "Qualified Local Labour"; type: discrete[2] = {

"Inadrquate". " Adequate"

1; position: (126 IO, 16105);

I

name: "Consuuction Support Facilities"; type: discrerr[2] =

BeliefNenc.ork Anaiysis of Direcr Cosr Hisk in Building Cànsrnlcr~on 183

C "Adequate", "Inadequaten

1: position: (16720, 16090);

1

node LcICnstrctnMrkt

name: "Local Construction Market": type: discrete[3] =

"Saturated". "Normal". "Poor"

\. 1 .

position: (19180, 16090); 1

node AvIbltyOEnrgy

name: "AvailabiIity of Energy": type: discrete[2] = {


}: position: (10180, 15115);

1

node Utilities {

name: "Utilities": spe: discrete[j] = C

"Presence of (location known)", "Presence of (location unknown)". "No presence of"

1; position: (12010, 15145);

1

node AreaAmuence {

name: "Area Affluence"; type: discrete[î] =

"Prosperousn, "Non-prosperous"

1: position: (23635, 16090):

1

node Ciroundconditions {

name: "Ground Conditions"; type: discrete[2] =

"Worse than Expected", "As expected or better"

1: position: (12970. 15 160):

1

nodr EnvmmntlSns~y

name: "Ecological Environment"; type: discrete[3] =

"Very sensitive".

Belief Nenvork Anaipis of Direct Cost Risk in Bidding Construction 184

"ModerateIy Sensitive", "Not Sensitive"

1; position: (14635, 15160):

1

node LndRltdNtrlDsstr

name: "Land Related Natunl Disaster"; type: discrete[2] =

{ "Likrly". "Unlikely"

1: position: (16690. 15 160);

1

node WeatherExtremes

narne: "Weather Eutremes": typer discrete[2] =

"Likelyn. "Unlikelp"

1: position: (19165. 15 175);

I

node Clirnate C

name: "Climaten; type: discrete[2] =

"Moderate", "Eutremc"

1: position: (23260, 15205):

1

node Geography {

name: "Geography"; type: discrcte[3] =

I "Rernote", "Rural". "Urban"

!: position: (210 IO, 151 75);

I

node Altitude t

name: "Altitude": type: discrete[2] = {

"High (>3000£i)", "Low (-3OOOtt)"

1: position: (24280, 15205):

1

node Geology {

narne: "Geology": type: discrete[2] =

"FavourabIe", "Unfavounble"

1;

Belief A1envork Analvsis of Direct COSI Risk in Bdd ing Consrnicrion 185

position: (22240, 15 190); 1

node BudgetRevisions i

name: "Budget Revisions"; type: discretel21 = !

"AIIowedn. "Forbidden"

1: position: (13870, 17875);

I

node FundingSource {

name: "Funding Source"; tvpe: discrete[3]=

"Privare", "Public". "Combination"

I; position: (10075, 17815);

1

node Owvnrr t

name: "Owner"; type: discrete[2] = t

"Flnancially stable". "Financially unstable"

1 : position: ( 12300. 17875);

node SiteSccurity I

name: "Site Security"; type: discrete[?] =

{ "Typical". "Atypicai"

1; position: (23260. 17845);

1

node SiteAccess C

narne: "Site Access": type: discrete[2]= {


1: position: (210 10, 17845):

1

node PhysclPrjctSz t

narne: "Physical Project Size"; type: discretel21 = {

"Large", "Srnall"

1; position: (1 5865. 17875);

I

Belief Nenvork Analysts of Direct Cosr Risk in Bzrildrng Cons~rnction 186

. . . . . . o o o o o o o o p

L LI id 'O id O O O - - - O - O O P

(1. 1, O. 1, 1, 1): O, O, 0~001,0.012,0.079.0251.0.38,0.777; (1. 1. 1. O, O, O): 0.002,0.022,0.113,0.281,0.333,0.19,0.052.0.007: (1. 1, 1, O, 0. 1): O, 0.001001.0.00900903,0.0650652,0217217~ 0.346346.0.264264,0.0970973; (1, 1, 1. O, 1-0): 0.0.00100 1,0.00900903,0.0650652,0.2172 I7,0.346346.0.264264,0.0970973; (1, 1- 1. O, 1, 1): O, O, 0.001,0.012,0.079.0.251,0.38,0.277; (1. 1. 1. 1, O, 0): 3,0~001001,0.00900903.0.06506510.217217,0346346.0.264264.0~0970973: (1, 1. 1. 1. O. 1): 0. O, 0.001,0.012. O-079,0.251,0.38,0.277; (1. 1, 1, 1. 1, O): O. O, 9.00l.0.012. 0.079.0.251,0.38,0.277: (1. 1, 1. 1, 1. i): 0,0,0.0.001, 0.019.0.1 17.0.353.0.51:

1

probabiIitv(Labour 1 Geography, QlfdLclLbr, Ovenime. LabourProductivity, Inflation. ConsuuctionDeIays) C

(O, O, O, O, 0.0): 0.51.0.353,0.117,0.019,0.001,0,0, O; (O, O, O, O. O, 1): 0.277.038,025-1.0.079.0~012,0.001. O, O; (O. O. O. O. 1. O): 0.277, C.38,0251,0.079.0-012,O.OOl. O, 0: (O. O, 0. O. 1. 1): 0.0970973.0.264264.0.346346,0317217. 0.0650652.0.00900903.0.00 1001. O; (0,0,0, 1, 0,O): 0.277, 0.38.0.251,0.079, 0~012,0.001.0,0; (O, O, O, 1, O, 1): 0.047037,0.179179.0.33033,0.293292,0.124124,0.025025,0~002002, O; (O, O. O, 1, 1.0): 0.047047, O. 1791 79.0.33033.0.292292, O. 124 124,0.025025,0.002002. O; (O, 0. O, 1, 1. 1): 0.007,0.052.0.19,0.333.0.281,0.113,0.022,0.002; (O, O, 1, O, O, O): 0.277. 038.0.251,0.079.0.0I2. 0.001, O, O: (O, O. 1. O. O, 1): 0.047047.0.I79l79, 0.33033,0.292292,0.124I24. 0.025025,0.002002. 0: (O, O, 1, O, 1,O): 0.047047,0.179179, 0.33033,0.292292,0.124124. 0.025025.0.002002, O; (O, O. 1, O, 1, 1): 0.007,0.052.0.19,0.333.0.28I, 0.1 13,0.022.0.002: (O. O. 1, 1. O, O): 0.037047.0.179 I79.0.33033. 0.292292.0.124 l24.O.O2502% 0.002002. O: (0,O. 1. I,O, 1):0.002,0.022,0.113.0.2SI.0.333.0.19,0.052,0.007: (0.0. 1, 1. 1, O): 0.002, 0 . 0 2 0.1 13.0.281.0.333, 0.19.0.052.0.007: (O, O, 1, 1, 1, 1): O. O70O2O02, 0.025025,0.124I24,0292292,0.33033.0.179179,0.047047; (O, 1. O. O, 0. O): 0.277.038.0.251.0.079.0.0I2.0.001, O, O: (O. 1. O, O, O. 1): 0.047047,0.179179,0.33033,0.291292, O. 123124.0.025025.0.002002. O; (O, 1, O, O, 1. O): 0.047047,0.179179,0.33033,0.292292, O. 124 l24,O.O2502j. 0.002002, O: (O, 1,0.0, 1, 1): 0.007,0.052,0.19. 0.333,0.281,0.113.0.022.0.002; (O, 1. O, 1, O, O): 0.047047,O. 179 179,0.33033,0.292292. O. 124 124,0.025025,0.002002, O; (O, 1, O, 1, O, 1): 0.002,0.022,0.113.0.281.0.333,0.19,0.052,0.007; (O. 1, O, 1. 1,O): 0.002,0.022,0.113,0.281,0.333. 0.19,O-052.0.007: (O, 1. O, 1. 1. 1): O, 0.002002,0.025025.0.124124,0.292292,0.33033.0.179179,0.017047; (O, 1. [,O, 0,O): 0.037047,0.179179,0.33033,0.292292.0.124124,0.025025,0.002002,0; (0, 1. 1.0.0, 1):0.002,0.022,0.113,0.281.0.333,0.19.0.052,0.007; (O, 1, 1, O, 1, O): 0.002.0.022.0.1 13,0.281.0.333.0.19,0.052,0.007~ (O, 1, 1. O, 1, 1): O, 0.002002,0.025025.0.124124.0.29192, 0.33033. O. 179 179.0.047047; (O, 1. 1. 1. O? O): 0.002.0.022,0.113,0.281.0.333.0.I9.0.0SZ,0.007: (O, 1. 1. 1, O, 1): 0,0.001001,0.00900903.0.0650652.0.217217. 0.346346.0.264264,0.0970973; (O. 1. 1, 1, 1, O): O, 0.00 1001,0.00900903,0.0650652, 0.2 17217. 0.346316. 0.264264,0.0970973: (O, 1, 1, 1, 1, 1): O, O, 0.001,0.012,0.079.0.251,038~ 0.277; (1. O, O, O, O. O): 0.393393,0.383383.0.179179,0.04004,0.00400/1, O. O- 0: (1, O, O, O, O. 1): 0.175.0.338,0.3 14.0.14.0.03.0.003. O. O; (1. O, O, O, 1, O): 0.175. 0.338,0.314,0.14.0.03.0.003, O, 0: (1,0,0,0. 1, 1): 0.047047,0.179179,0.33033,0.292292,0.I24124.0.025025.0.002002.0; ( 1. O, O, 1. O, O): 0.0970973, 0.264264. 0.346346,O.Z 1721 7.0.0650652. 0.00900903, 0.00 LOO 1. O: (1, O, O. 1. O. 1): 0.018981,0.103896,0.270729.0.337662,0.201798.0.0579122.0.00799209,0.000999009; (1. O. O, 1. 1.0): 0.018981.0.103896,0.270729,0.337662.0.201798.0.0579422, 0.00799209,0.000999009; (1.0,0, 1, 1, 1): 0.002. 0.022.0.1 13,0.281,0.333,0.19,0.052,0.007; (1. O, 1, O, O, 0): 0.0970973,0.264264.0.346346,0.217217,0.0630652,0.00900903,0.00 100 1, O; (1, O. 1, O, O, 1): 0.018981.0.103896,0.270729,0.337662,0301798,0.0579122.0.00799209.0.000999009; (1. O, 1.0. 1, O): 0.018981. 0.103896.0.270729.0.337662,0.201798, 0.0579122.0.00799209,0.000999009; (1, O. 1, O, 1, 1): 0.002, 0.022,O.I 13.0.281.0.333,0.19.0.052. 0.007: (1. O. 1, 1. O. 0): 0.007.0.05Z, 0.19,0.333.0.281.0.113,0.022.0.002; (1. O, 1, 1, O, 1): 0.000999009,0.00799209,0.0579422,0.20 179S,0.3376627 0.270729,O. 103896, 0.0 1898 1; (1,O. 1, 1, 1. O): 0.000999009, 0.00799209, 0.0579422.0.201798.0.337662, 0.270729,0.103S96, 0.018981: (1. O, 1. 1. 1, 1): O. 0.00 1001,0.00900903,0.0650652.02 172 17, 0.346346.0.263263,0.0970973; (1, 1. O, O. O. 0): 0.0970973,0264264,0.346346,0.217217,0.0650652.0.00900903,0.001001. O; (1, 1, O, O, O, 1): 0.018981.0.103896,0.270729,0.337662,0.201798, 0.0579422,0.00799209,0.000999009; (1, i, O, O. 1.0): 0.0 1898 1. O. 103896,0.270729,0.337662,020 1 ï38,0.0579422,0.00799209,0.000999009; (1, 1. O, O, 1, 1): 0.002,0.022,0.113,0.281,0333,0.19,0.052,0.007; (1. 1. O, 1, 0, 0): 0.007,0.052, 0.19.0.333,0.281,O.I 13, 0.022,0.002; (1, 1, O. 1. O, 1): 0.000999009.0.00799209. 0.0579422.0.201798, 0.337662. 0.270729, 0.103896, 0.018981; ( 1. 1. O, 1. 1. O): 0.000999009.0.00799209.0.0579322.0.201 798.0.337662, 0.270729, O. 103S96.0.01898 1 ; (1. 1, O, 1, 1. 1): O, 0.00 1 O0 1,0.00900903.0.0650652,0.2 172 17.0.346336, 0.264264,0.0970973; (1 . 1. 1,0, O. O): 0.007,0.052.0.19.0.333.0.281.0.113.0.022,0.002;

Belief i\'enrork Anabsis of Direct Cos1 Risk in Building Consrrucrion 188

(I, I , 1.0.0. 1): 0.000999009,0.00799209,0.0579422,0.20 l798.0.33766X 0.270729,0.I03896,0.0 1898 1; (I, I , I , 0, 1.0): 0.000999009,0.00799209,0.0579422,0.201798,0.337662.0.270729,0.103896,0.018981; (1, L, I. 0. 1, 1): 0,O.OO 100 1, 0.00900903.0.0650652 0 2 172 17,0.346346,0264264,0.0970973; (1, 1, 1, L O , 0): 0,0.002002,0.025025,0.124124,0.292292,0.33033,0.179179,0.M7047; (1, I, I, I , 0, 1): 0.0,0.003,0.03,0.14.0.314,0.338,0.175: (I, I, 1, 1, I, 0): 0.0,0.003,0.03,0.14,0.3 14.0.338.0.175; (1. I, I, 1. 1, I): 0.0,0,0.004004,0.04004.0.179179,0.383383,0.393393; (2,0,0,0,0,0): 0.277,0.38,0.251.0.079,0.012,0.001.0.0: (2,0,0,0,0, 1): 0.0970973,0264264,0.346346,0.217217,0.0650652,0.00900903,0.001001.0; (2.0,0,0, I, 0): 0.0970973,0.264264,0.346346.0217217.0.0650652,0.00900903,0.00 I00 1.0; (2.0.0.0. I , I): 0.007,0.052,0.19,0.333,0.281,0.113,0.022,0.002; (2,0,O, 1.0.0): 0.047047.0.1791 79. 0.33033,0.292292,0 I24 124.0.025025.0.002002.0; (2,0,0, 1.0, I): 0.007,0.052,0.19,0.333,0.281,0.113,0.022,0.002: (2,0,0, 1, 1.0): 0.007,0.05& 0.19,0.333.0.281,0.113,0.022,0.002; (2.0,O. 1, 1. 1): 0,0.002002,0.025025.0.124 l24,O.292292,O.33O33,O. 179 l79.O.O47O47; (2.0, I, 0.0.0): 0.047047,0.179179. 0.33033,0293292.0.124124,0.02S025,0.002002.0; (2.0, I , O,O, 1): 0.007,0.05L 0.19,0.333,0.281,0.113,0.022,0.002; (2.0, 1.0, 1.0): 0.007,0.052,0.19,0.333.0.28 1.0.1 13.0.022,0.002; (2.0, I. 0, I, I): 0,0.002002,0.025025,0.124I24,0.292292,0.33033,0.179 179,0.047047: (2.0, I, LO, 0): 0.002,0.022,0.113,0.281,0.333,0.19,0.052,0.007; (2.0, 1. 1.0. 1): 0,0.002002,0.025025,0.124 124.0.29Xl92, 0.33033,O.I 79 179, 0.047047: (2.0, 1. 1, I, 0): 0,0.002002,0.025025,0.124124,0292292,0.33033,0.179 179.0.047047; (2.0, I, I, I, 1): O,O,O.OOL, 0.012,0.079,025L, 0.38,0.277; (2, 1, 0, 0, 0,O): 0.047047,O. 179 179, 0.33033.0.292292,O. 124 l24.0.025025, 0.002002.0; (2, I. 0.0.0. 1): 0.007, 0.052,0.19.0.333,0.281.0.113,0.022,0.002; (2. 1, 0,O. 1.0): 0.007, 0.052,0.I9,0.333,0.281.0~113.0~037~ 0.002: (2, l.O,O, I , I): 0,0.002002,0.025025.0.124124.0.292292,0.33033.0.179 179.0.047017; (2, I , 0, 1.0.0): 0.002, 0.022. 0.1 13, 0.281,0.333,0.19.0.052,0.007: (2, 1,O. I, 0, 1): 0,0.002002,0.025025,0.124124,0.292292,0.33033.0.179 179.0.047047; (2, 1,0, 1, I , 0): 0,0.002002,0.025025,0.124124,0.292292,0.33033,0.179 179,0.047037; (2. 1,0, I , I , I): O,O, 0.001.0.012, 0.079,0.251.0.38, 0.277; (2, I , I , 0.0.0): 0.002.0.022. 0.1 13,0.281.0.333,0.19,0.052.0.007: (2, I, I. 0.0, 1): 0,0.002002,0.025025,0.124 124.0.292292,0.33033.0- 179 179.0.047047; (2, 1, I, 0, I , 0): 0,0.002002,0.023025.0.124124.0.292292,0.33033,0.179179.0.047047; (2. I. I. 0, I, I): 0,0.0.001,0.012,0.079.0.251,0.38.0.277: (2, 1. 1, I, 0.0): 0, O.OOIOOI, 0.00900903,0-0650652.0.217217,0.346346.0.264264.0.0970973; (2. 1. 1, I , 0, I): 0,0,0.001.0.0~2.0.079,0.251,038,0.277: (2. 1. I. I, 1,O): 0,0,0.001.0.012.0.079,0.251,0.38,0.277; (2, 1, 1. I, I, 1): 0,0,0,0.001,0.019.0.1 17.0.3S3,0.51:

1

probability(Materia1 I Materialshortage, CnstrctnblrktEscltn, Materialwaste, Scopecreep. DesignChanges. ValueEngineering)

(O,O, O,O, 0, 0): 0.51, 0.353.0.1 17,0.019, 0.001, 0, 0.0: (0, C, O,O,O, 1): 0.277,0.38,0251,0.079.0.012,0.001,0.0; (O,O, 0.0, I, 0): 0.277,038,0.25 1,0.079,0.012.0.001,0,0; (0.0.0,O. I, I): 0.0970973, 0.264264.0.346346,0.2~7217,0.0650652, 0.00900903,0.001001,0: (0.0.0. I,O, 0): 0.277,0.38, 0.251,0.079,0.012,0.001.0.0; (0.0.0, I. 0, 1): 0.0970973,0264264,0.316346,0.217217,0.0650652, 0.00900903,0.00 100 1,O: (0.0.0, 1 , 1,O): 0.047047,0.179179,0.33033,0.292292,0.L24124,0.025025,0.002002, 0; (O,O,O, I , 1, I): 0.007,0.052,0.19,0.333,0.281,0.113,0.022,0.002; (O,O, 1,O.O. 0): 0.277,0.38.0.251,0.079,0.012,0.001.0,0; (O,O, I, 0.0, I): 0.0970973,0.264264,0.346346,0.217217,0.0650652,0.00900903,0.00 1001.0; (O,O, 1.0, I, 0): 0.047047,0.179179,0.33033,0.292292.0.124124.0.025025.0.002002,0; (0.0, 1.0, I, I): 0.007.0.052,0.19.0.333.0.281,0.113,0.022.0.002: (0,O. 1. 1,0,0): 0.047047,0.179 17% 0.33033.0.292292.0.124124,0.025025,0.002002,0: (0,O. I , 1.0. I): 0.007,0.052,0.19,0.333.0.281,0.113,0.022.0.002; (0, 0, 1, 1, 1.0): 0.007,0.052, 0.19,0.333,0.281, 0.1 13,0.022,0.002; (0.0, 1. 1, I, I): 0,0.002002,0.025025,0.124124,0.292292,0.33033,0.179 I79.O.W7047; (0, I , 0.0.0.0): 0.277,0.38.0.251,0.079,0.012, 0.001.0,O; (0, I, 0,0,0, I): 0.047047,0.179179,0.~~033,0.292292,0.12-i124,0.02S025, 0.002002,O; (0, I, 0,0, I, 0): 0.047037.0.179 179, 0.33033,@.292292,0~124124,0.025025,0.002002,0; (0, 1.0.0, I. 1):0.007,0.05~0.19,0.333,0.281,0.l13,0.022,0.002: (0, 1, 0, I, 0.0): 0.047047, 0.179 179, 0.33033,0.292292, 0.124 124, 0.025025,0.002002,0; (0, I. 0, I, 0, 1): 0.007, 0.052,0.19, 0.333,0.281, 0.1 13,0.022,0.002; (0, I, 0, I, 1.0): 0.002,0.022,0.113,0.281,0333,0.19,0.052.0.007; (0, 1.0, 1. 1, 1): 0,0.002002,0.025025,0.124124.0.292292,0.33033,0.179179,0.047047: (0, I, 1,0, I), 0): 0.047047,0.179179,0.33033,0.292292,0.124124,0.025025,0.002002,0; (0, I, I, 0.0, I): 0.007,0.052, 0.19,0.333,0.281,0.113,0.022,0.002: (0, 1. 1.0, 1,0):0.002,0.022,0.113,0.281,0.333,0.19,0.052,0.007:

Belief XencporX- Analysis of Direct Cost Risk in Bidding Consrnrcrion 189

(O, 1. 1. O, 1, 1): O, O.OO2OO3 0.025025,0.124124,0.29~92,0.33033.0.I79179,0.047047: (O, 1, 1, 1, O, O): 0.002,0.022,0.1I3,0.281,0333,0.19,0.052,0.007~ (O, I , 1. I, 0, 1): 0,0.002002,0.025025,0.124124,0292292, 0.33033.0. t 79179.0.047047; (0, 1, 1. 1, 1.0): 0,0.002002,0.025025.0.124124,0292292,0.33033. O. 179 l79,0.047047; (O, 1, 1. 1, 1. 1): O. 0,0.001,0.012,0.079.0.251,0.38.0.277; (1,0,0,0. 0,O): 0.277,038,0.251,0.079, 0.0I2,0.001,0,0; (1. O, O. O, O, 1): 0.047047, O. 179179.0.33033,0.192292, O. 124 124,0.025025.0.002002. O; (1. O, O, O. 1. O): 0.047047,0.179179,0.33033,C).292292.0.124124,0.025025,0.002002, O; (I.0,O.O. 1. 1):0007,0.052.0.19.0.333,0.281,0.113,0.022,0.002: (1. O, O, 1, O, O): 0.C47047,0.l79179,0.33033.0292292,0.124123,0.015025.0.002002, O: (1 , O. O. 1, O, 1): 0.007,0.052.0.19.0.333,0.28I,O.lI3. 0.022,0.002; (1.0, 0, 1. 1.0): 0.002,0.022,0.113.O.2S~, 0333,0.19.0.052,0.007; ( 1, O, O, 1. 1, 1): 0.0.002002,0.025025,0.1Z4123,0292292,0.33033,0.179 179.0.047047: ( 1- O, 1. O. O, 0): 0.047047.0.179 I79,033033,0.292292,0.124 124,0.025025,0.002002.0: (1, O, 1, O. O, 1): 0.007,0.052,0.I9,0.333- 0.281,O.I 13, 0-022.0.002: (1, O, 1, O. 1, O): 0.002.0.02L 0.1 13,0.281.0333,0.19, 0.052.0.007; (1. O. 1, O. 1, 1): O. 0.002002,0.025025. O. 124 124, 0292292.0.33033.0.179 179.0.047047; (1, O. 1. 1, O, O): 0.002,0.022,0.113.0.281.0333,0.19.0.052.0.007: (1, O, 1. 1. O, 1): O, 0.002002.0.025025.0~123 124. 0292292.0.33033. 0.179 179.0.047047; (1, O. 1, 1. 1. O): O. 0.002002.0.025025.0.124123,0.29192.0.33033.0.179 179.0.047047: (1,O. 1, 1. 1. 1): O. O. 0.001.0.0L2,0.079.0251,0.38,0.277: (1. 1. O, O, O, O): 0.047047,0.179179, 0.37033,0.292292.0.124121.0.025025.0.002002. O; (1. 1. O, O. O. 1): 0.002, OAO22, 0-1 13,0.281.0.333.0.19,0.052,0.007; (1. 1. O, O, 1. 0): 0.002,0.022,0.1 13,0.281.0333.0.19.0.052, 0.007; (1, 1, O. O. 1, 1): O, 0.002002,0.025025,0.I24 124,0.292292,0.33033, O. 179 179,0.0470.17: (1. 1. O, 1. O, O): 0.002,0.022,0.113, 0.281.0333. 0.19.0.052.0.007: (1. 1. O, 1. O, 1): O, 0.002002,0.025025, O. 124124,0.292292,0.33033, O. 179 179.0.047047; (1, 1, O, 1. 1, O): O, 0.001001,0.00900903.0.0630652,0.2 1721 7,0.346346,0.264264.0.0970973; (1, 1. O, 1, 1. 1): O, O, 0.001,0.012, 0.079, 0251,0.38,0277: (1. 1, 1, O, O, O): 0.002,0.022,0.113.0.281,0.333. 0.19, 0.052.0.007; (1, 1. 1, O, O, 1): O, 0.002002,0.025025. O. 124 124, 0292292.0.33033, O. 179 I79.O.W7047; (1, 1. 1. O, 1, O): O, 0.001001,0.00900903. 0.0650652,02 172 17.0.346346. 0.261264,0.0970973: (1. 1, 1. O, 1, 1): O, O, 0.001,0.012,0.079,0.251,0.38,0.277; ( 1. 1. 1. 1, O. O): 0.0.001001.0.00900903.0.0650652.021 72 17.0.346346. 0.264264.0.0970973; (1. 1, 1. 1. O, 1): O, O, 0.001.0.012,0.079,0~251,0.38,0277; (1. 1. 1. 1. 1, O): O. O, 0.001.0.012.0.079. 0.251,0.38.0.277: (1. 1, 1. 1, 1, 1): O, O,O, O.OOl.O.Ol9,O.l l7,0.353,0.51;

I

(O, O, O, O): 0.6,0.4; (O. O, O, 1): 0.9, O. 1; (3, O, 1. O): 0.6.0.4; (O, O. 1, 1): 0.83,0.17; (0. 1. O, O): 0.53.0.47; (O. 1, O. 1): 0.7,03; (O. 1, 1. O): 0.5.0.5: (O, 1, 1. 1): 0.7.0.3; (1. O, O, O): 0.6.0.4: (I,O, O, 1): 0-67.0.33; (1. O, 1, O): 0.47.0.53: (1, O, I , 1): 0.73.0.27; (1, 1. O, O): 0.4.0.6; (1, 1, O, 1): O.6,O.a; (1. 1. 1, O): 0-17.0.83; (1. 1. 1. 1): 0.47,0.53;

(O, O, O): 0.67, 0.33; (O, O, 1): 0.23,0.77; (O, 1. O): 0.44.0.56; (O. 1. 1): O. l6,O.83; ( 1. O, O): 0.54,O. 16; ( 1, O. 1): O-56,O.M; (1, 1, O): 0.77.0.23; ( 1, 1, 1 }: 0.33,0.67:

1

Belle/ Nehvork Analysis of Direct Cost Risk in Building Construcrion 190

probability(FieldClaims 1 DefectiveWork GroundConditions, Traddoordination) {

(O, O, O): 0.67.0.33: (O. O, 1): 0.83. O. 16: (O. 1. O): 0.23,0.77; (O. 1. 1): 0.56.0.41; ( 1. O, 0): 0.44.0.56; (1, O, 1): O.77,0.23; (1, 1 , O): 0.l6.O.84; (1, 1, 1): 0.33.0.67;

1

probability(DelriyC1airns I LongWorkStoppages, Ovenime. ConstmctionDeIays) l

(O. O. O): 0.84,0.16: (0, O, 1): 0.77,0.23; (O, 1. O): 0.56,O.M; (O. 1. 1): 0.33.0.67; (1, O. O): 0.67.0.33: ( 1,O. I ): 0.44,0.56; ( 1 , 1, O): 0.23,0.77; (1. 1. 1): 0.16,0.84;

1

probability(PMClaimsMitigation 1 PM. QifdKyPMPnnnl) t

(O. O): 0.44.0.56; (O, 1): 0.52.0.48; (1, O): 0.45.0.52; (1. 1): 0.56.0-44;

1

probability(Conrrac1Clauses 1 Cnuctr&mntTyp) I

(O): 0.85. O. 15. O; ( 1): 0.65.0.3.0.05; (2): 0.77.0.23, O; (3): 0.04,0.9,0.06;

1

(O. O, O): 0.93.0.07; (0. O, 1): 0.7,0.3: (O. 1. O): 0.77.0.23; (O, 1, 1): 0.3, 0.7; (1. O, O): 0.9, 0.1; ( 1, O, 1 ): 0-6.0.4; ( 1. 1. O): 0.77.0.23; (1- 1, 1): 0-1, 0-9:

1

probability(ConstructionDelays 1 FailureDelays. EnvironrnentalDelays, DesignDelays, LogisticsDelays, LabourDelays) {

(0, 0,O: O, O): 0.87, 0.13; (O, O, O. O. 1): 0.87. 0.13; (O, 0. O, 1, O): 0.87.0-13; (O, O. O, 1. 1): 0.87, 0.13; (O, O. 1. O, O): 0.87. 0.13: (O, O, 1, O, 1): 0.87. 0.13: (O, O, 1 , 1, O): 0.87, O. 13; (O, O, 1, 1, 1): 0.87.0.13; (O, 1, o. o. O): 1. O; (O, 1, O, 0, 1): 1, O;

Belief Nenvork Anaiysis of Direct Cosr Risk in Btrilding Consrnrction 191

(O, l,O, 1.0): 1,o: (O, 1. O, 1. 1): 1, O: (O, 1.1.0,O): 1.0: (O, 1, 1, o. 1): 1 . O; (O. 1. 1- 1. O): 1- O: (O* 1- 1. 1.1): 1.0; (1.0,0,0.0):0.87,0.13: (1, O, 0. O. 1): 0.87,0.I3: (1. O, O. 1. O): 0.87,0.13: (1,O.O. 1, 1): 0.87.0.13; (1.0. I,O,0):0.87,0-13; (1.0, 1. O, 1): 0.87, 0.13; (1.0, t. 1,O): 0.87.0.13: (1.0, 1, 1, 1): 0.87.0.13; (1. 1.0,0.0):0.87.0.13: (1, 1. O, O, 1): 0.83,0.17; (1, 1. O. 1. O): 0.73.027: (1. 1, O, i, 1): 0.7.0.3: (1. 1, 1. O. O): 0.77.0.23; (1. 1. 1. O, 1): 0.47.0.53; (1, 1, 1, !,O): 0.73.0.27; (1. 1, 1, 1, 1): 0.01. 0.99:

1

(0. O. O): 0.84, O. 16; (O, O. 1): 0.77.0.23; (O. 1, O): 0A67. 0.33: (O, 1, 1 ): 0.34.0.56; (1, O, O): 0.56,0.44; (1, O, 1): 0.33, 0.67; (1. 1. O): 0.23.0.77; (1. 1, 1): 0.16.0.84:

I

(O, O. O, O): 0.97.0.03: (O, O, O. 1): 0.4,0.6: (0, 0, 1. 0): 0.77,0.23; (O, O, 1. 1): 0.06.0.94: (O. 1, O, 0): O. 12.0.88; (O. 1. O, 1): 0.0 1. 0.99; (O. 1, 1, O): 0.0 1. 0.99; (O, 1, 1, 1): o. 1; (1, o. O, O): 1, O; (l,O,O. 1):0.99, 0.01; (1.0. 1. O): O.99,O.Ol; (1, O. 1. 1): 0.88.0.12: ( 1 , 1. O, O): 0.94,0.06; (1, 1. O, 1): 0.23.0.77; ( 1, 1 1. O): 0.6,0.4: (1, 1. 1, 1): 0.03,0.97;

1

Belief Xenvork Anafysis of Direct Cosr Risk in Birilding Constnrction 192

probability(LogisricsDelays 1 CnstrcuiOpruisInufmc. MateriaIsDelivery) (

(O. O): 0.52.0.48; (O, 1): 0.56,0.44; (1, O): 0-44.0.56; (1. 1): 0.48.0.52;

1

probabili&(DesignDelays 1 DesignSubmittal, DesignChanges)

(O, O): 0.52. 0.48: (O, 1 ): 0.44.0.56; ( 1. O): 0.56.0.44: (1. 1): 0.48.0.52;

1

probabiIity(EnvironrnentdDe~ays 1 WeatherExuemes. EnvrnrnntlSnstvty, LandDelays) (

(O, O, O): 0.96,0_04; (O. O. 1): 0.93.0.07: (O. 1.0): 0.7 1,029: (O. 1, 1): 0.57,0.43: (O. 2.0): O. 19.0.8 1: (O, 2. L): O. 1 1,039: (1, O. O): 0.89, O. 1 1; (1, O. 1): O.Sl,O.l9: (1. 1. O): 0.43.0.57; (L, 1, 1): 029,0.71; ( : . 2, O): 0.07,0.93; (1.2. 1): 0.04.0.96;

1

probability(LandDe1ays 1 LndRltdNtrIDsstr, G~ology, GroundConditions) (

(0. O. 0): 0.77.0.23: (O, O. 1): 0.33.0.67: (O. 1. O): 0.84, O. 16: (O. 1. 1): 0-56.0.44; (1. O. O): 0*4,0.56; (1. O. 1): 0.16.0.84; (1. 1. O): 0.67.0.33; (1, 1. 1): 0.23.0.77;

1

(O, O. O, O): 0.77.0.23: (O. O, O, 1): 0.73.027; (O. O. 1, O): 0.77,O.U; (O, O, 1. 1): 0.5.0.5; (O, 1, 0. O): 0.6.0.4; (O. 1.0. 1): 0.47,0.53: (O. 1, 1. O): 0.43.0-57: (O, 1, 1, 1): 0.27,0.73; (1, O. O. 0): 0.9, 0.1; (1, O. O, 1): 0.73.0.27; (1. O, 1, O): 0.87,0.13; (1, O, 1, 1): 0.67.0.33; (1, 1, O, O): 0.63.0.37; (1, I , O. 1): 0.57,0.43; (1. 1. 1. O): 0.5.0.5; (1, l7 1. 1): 0-4.0-6;

)

probability(Short8reaks 1 Climate, LbrInjrsAccdnrs. StblEqpmntAvIblty, MaterialShonage) I

(O. 0. O. O): 0.77.023: (O. O, 0. 1): 0.0 1.0.99; (O, O, 1. O): 0.99,O.O 1;

Belie/Nenvork Anafysis 01 Direct Cost Risk in Btrilding Construction 193

(O, O. 1. 1 ): 0.6.0.4: (O, 1. O, 0): 0-06.0.94; (O. 1.O.l):O. 1; (O, 1. 1, O): 0.88.0.12; (O, 1. 1. 1): 0.03,0.97; (1. O. 0,O): 0.97,0.03; (1.0. O. 1): O. 12.0.88; (1, o. 1. O): 1. O: (1, O. 1. 1): O.94,O.O6; (1, 1.0.0): 0.4,0.6: (1, 1, O, 1): 0.01,0.99: (1. 1. 1, O): O.99,O.Ol: (1. 1. 1. 1):023.0.77:

I

probabili&(labourCongestion 1 CnstrctnOprtnslntrfmc. TrafficCongestion. NmbrOfiVrkrsOnSt) (

(O, O, 0): 0.84, O. 16; (O, O, 1): 0.77,0.23; (O, 1, O): 0.67.0-33; (O, 1, 1): 0.4,0.56; ( 1. O, O): 0-56.0.4; (1. O, 1): 0.33.0.67; (1. 1- O): 023.0.77: (1, 1. 1): 0.16,0.83;

1

(O, O, O, 0): 0.0 1.0.99: (O, o. o. 1): o. 1: (O. O. 1.0): 0.12.0-88: (O, O, 1, 1): 0.0 1.0.99: (O. 1, O, O): 0.77.023; (O, 1. O, 1): 0.06.0.94; (O, 1, 1, O): 0-97.0.03; (O, 1, 1. 1 ): 0.4,0.6; (1, O. O. O): 0.6. 0.1; (1. O. 0. 1 ): 0.03.0.97: (1, O. 1. O): 0-94.0.06; (1, O. 1. 1): 0.23.0.77; (1. 1. 0. O ) : O.99,O.OI: (1, 1, O. 1): 0.88.0.12; (1, 1. 1, O): 1, O; (1, 1, 1. 1): 0.99,O.OI;

1

probabiiity(WrkQnttyDvtns 1 DefectiveWork DesignChan~es, Groundconditions, TnntRqrmntChns DaipQuality) {

(O,O,O,O,O): 0.93.0.07; (O, O, O, O, 1): 0.93, 0.07: (O. O, O. 1. O): 0.93,0.07; (O. O, O, 1. 1): 0.93. 0.07: (O, O. O, 2. O): 0.93. 0.07; (O, O, O, 2, 1): 0-93.0.07; (O, O, 1. 0. O): 0.93.0.07: (O. O, 1, O. 1): 0.93.0.07: (O, O, 1, 1,O): 0.93.0.07: (O, O, 1, 1, 1): 0-93.0.07; (O, O, 1.2, O): 0.93,0.07; (O, O, i . 2. 1): 0.93.0.07; (O. 1. O, O, O): 0.23.0.77; (O, 1, O, O, 1): 0.23,0.77; (O, 1.0. 1, O): 0.23.0-77; (O. 1. O, 1, 1): 023.0.77: (O, 1. O, 2, O): 0.23,0.77; (O. 1, O, 2. 1): 0.23.0.77; (O. 1, 1. O, O): 023.0.77: (O. 1. 1. O. 1): 0.23-0.77: (O, 1, 1, 1. O): 0.23,0.?7;

Belief ~Venvork Anabsis of Direcr Cosr Risk in Building Consrnrction 194

(1, 1, O, 1): 057.0.43; (1, 1. 1. O): 0.63.037: (1. 1, 1, 1): 0-83.0-1 7;

1

probability(EqprnntPrdctvty 1 Altitude. GroundConditions, StblEqpmntAvlblty)

(O. O. O): 0-7.0.3; (O. O. 1): 0.83, O. 17; (O. 1. O): 0.3.0.7; [O, 1. 1): 0.7.0.3: ( 1. O, O): 0.63.0.37: (1. O, 1): 0.83,O. 17: (1- l7 O): O.I.O.9; (1, 1. 1): 0.6.0.4;

1

(O): 0.23,0.77; ( 1): O. 15,O-85;

I

probabil i~(A.rchlgclSrvy) {

0.5.0.5; 1

(O. 0. O): 0.57,0.43; (0. O, 1): 0.3.0.7; (O, 1.0): 0.35,0.65; (O. 1, 1 ): 0.03,0.96: (1, O, O): 0.87, O. 13; (1, O. 1): 0-7.0-2; (1- 1. O): 0.6.0.4: (1, 1. 1): 0.2,0.8:

probability(TraffTcCongestion PhysclPrjctSz, Cmptn:ActvtyOnSt, NrnbrOfiVrkrsOnSt. SiteAcces2 s

(O, O. O, O): 0.55, 0.45: (O. O, O. 1): 0.93, 0.07; (O, O, 1. O): 0.53.0-47; (O, O, 1, 1): 0.8. 0.2; (O. 1. O. O): O. 17.0.83: (O, 1, O. 1): 0.27.0.73; (O. 1. 1. O): O.l3,0.87; (O. 1. 1. 1): 0.27.0.73; ( 1 . O, O, 0): 0.6, 0.4; ( [ , O, O, 1 ): 0.6,0.4; (1, O. 1. O): 0.6, 0.4; ( i , O, 1, l ): 0.6,O-4: (1. 1, O, O): 0.5,0.5; (1, 1, O. 1): 0-5. 0.5: ( 1. 1, 1. O): 0.27.0.73; (1. 1, 1, 1): 0.37.0.63;

1

Beliej Nenvork Analysis of Direct Cosr Risk in Building Consrnrction 196

(O): 0.8,02; (1): 0,13,0.87;

I

probability(CostAccounting 1 PM) f

(O): 0.83, O. 17: (1): O. 13.0.87;

1

(O, 0. O): 0.27.0-73; (O, O, 1): 0.83.0.17; (O, 1. O): 0.3,0.7; (O, 1, 1): 0.75.0.25: (1, O, O): 0.27,0.73: ( l+ O, 1): 0.8,0.2: ( 1, 1. O): 0-27.0.73: (1. 1, 1): 0.67.0.33;

1

(O): 0.83, O. 17; ( 1 ): 0.33,0.67;

1

probability(CprtvEnvmmnt 1 QlfdKyPMPrsnnl. PM)

(O, O): 0.83. O. 17: (O, 1): 0.43.0.57; ( 1,O): OV6,0.4r (1. 1): 0.2, 0.8:

1

probability(PM 1 QlfdKyPMPrsnnl, PMWorkFamiliarity)

(O, O): 0.86.0.14: (O. 1): 0.6,0.4: (1,O): 0.6,0.4; (1, 1): 0.23.0.77;

(O): O. 13.0.87; ( 1): 0.7.0.3;

i

(O): 0.7.0.3: (1 1: 0.77.0-73;

1

Belief Arenvork Analysis of Direct Cosr Risk in Building Constnrcfion 197

probability(Va1ueEngineering 1 ConstructionDelays. PM, BudgetRcvisions)

(O, O. O): 0.4,O.O; (0. O, 1): 0.7,0.3; (O, 1. O): 0.3,0.7: (O, 1. 1): O. 15,0.85: (I.0,O): 0.33.0.67; (1, O. 1): 0.73.0.27; ( L, 1.0): 0.27.0.73: (1, 1, 1): O.6,OA;

1

probability(DesignChmges 1 CmplxtyCnsuctbleOfDsg- ScopeCreep. DesignQuality) \

(O. O, O): 0.53.0.47: (O, O, 1): 0.93,0.07: (O. 1, O): O. 13.0-87; (O, 1, 1): 0.8,02; (1. O, O): 0.35.0.65: (1, O. l): O-7,0.3; (1, 1. O): 0.04.0-96; (1. 1, i): 0.6. OA;

1

probability(DesignSubmitta1I ScopeCreep. DsgnTmCrdntn) I

(O. O): 0.4.0.6; (O. 1): 0.13,0.87: (1. O): 0.7, 0.3; (1. 1): 02.0.8;

1

probability(DesignQuality 1 ScopeCrerp, DsgnTmCrdntn, CnstrctnTchnlgyRqrmnfs) {

(O, O. O): 0.37.0.63; (O, O. 1): 0.7.0.3; (O, 1.0): 0.2,o.s; (O. 1. 1): 0-3.0.7; ( 1. O. 0): 0.73.0.27: (1, O. 1): 0.93. 0.07: ( 1, 1. O): 0.23, 0.77; (1. 1- 1): 0.3.0.7:

I

probability(ScopeCreep 1 DsgnTmCrdntn. TnntRqmntChng)

(O, O): 0.8, 0.2 (O, 1): 0.3, 0.7; (O. 2): 0.14.0.86: (1. O): 0.97.0.03: (1. 1): 0.55,0.45; (1.2): 0.35,0.55;

1

I (O): 0.7,0.3; (1): 0.1,O.g;

1

Beiief A'e fivork Analysis of Direct Con Risk in Building Consrnrction 198

probability(Regulato@enalties f EnvrnrnntlSns~vtv) {

(O): 0.63. 037; (1): 0.47, 0.53; (2): O. 1,0.9;

1

probability(PerrnitsRequired 1 Utilities) {

(O): 0.43.0.57; (1): 0.7. 0.3: (2): 0.04.0.96;

1

probability(GvrnrnntSpndngOnCnstrc~n 1 Government)

(O): 0.5.0.5; (1 ): 0.43.0.57:

i

probability(1ntmtntMrktPrcs 1 FrgnPrchsdGds. ExchangeRates) {

(OI 0): 0.97,0.03; (O. 1): O. 1.0.9; (1,O): 0.01. 0.99: (1, 1): 0-04.0-96:

probability(CnstrctnMrktEscItn 1 LclCnstrctniLIrkt. GvmrnntSpndngOnCnstrctn. Inflation)

(O, O, O): 0.93, 0.07; (O, O, 1): 0.8.0.2; (O. 1, O): 0.6.0.4; (O. 1. 1): 0.63,0.37; (1.0. O): 0.7,0.3: (1. O, 1): 0.47,0.53; (1, 1, O): 0.6.0.4; (1, 1, 1): 0.13, 0.87; (2. O. O): 0.4.0.6; (2, O. 1): 0.37,O-63; (2 . 1. O): 0.6.0.4; (2- 1. 1): 0.1.0-9:

1

probability(Int1ation 1 GvmmntSpndngOnCnstrctn) (

(O): 0.53.0.47; ( 1): O. 17.0.83:

1

probabiIity(TasRates 1 Govemment)

probabil ity(ExchangeRates) (

0.5.0.5; 1

probability(FrgnPrchsdGds 1 StblEqpmntAvlbIty. ExchangeRates) {

(O, O): O. 1.0.9; (O, 1): 0.2,0.8;

Belief Nenvork Analysis of Direct Cost Risk in Btrilding Consrrucrion 199

(1, O): 0.77.023; (1. 1): 0.87.0-13;

I

{ (O): 0.3.0.7:

probabiIity(StbiEqprnntAv1blty 1 MtrlEqprnntLss. LcICnstrctnMrkt. Geography) t

(O, O, O): 0.07.0.93; (O, O, 1): 0.07.0.93: (O, O, 2): 0.07.0.93; (O, 1. O): 0.6,0.3: (0. 1. 1): 0.37.0.63: (O. 1 , 2): 0.2.0.8; (O. 2. O): 0.4.0.6; (O. 2. 1): 0.55.0.45; (O, 2.2): 0.3.0.7; ( 1.0. O): 0-07.0.93: (1, O. 1 ): 0.07.0.93; ( 1. O, 2): 0.07.0.93; (1. 1. O): 0.7.03; (1, 1, 1): 0-55.0-45: (1. t . 2): 0.2,o.s; (1.2, 0): 0.75,0.25; (I,2, 1): 0.75, 0.25; (1- 2,2): 0.3.0-7:

t

probabiIity(Q1fdLclLbr 1 LclCnstrctnMrkt) (

(O): 0.8,02; (1): 0.37.0.63; (2): 0.47.0.53;

1

probability(CnsrrctnSppnFclts 1 LclCnstrctnMrkt AreaAf-fiuence) I

(O. O): 0.47.0.53; (O. 1 ): 0.4.0.6; (1. O): 0.53.0.47; (1, 1): 053.0.47; (2. O): 0.67,0.33; (2, 1 ): 0.63.0.37:

1

probabilicy(Avlblty0fEnrgy 1 Geography) i

(O): 0.83. O. 17: (1): 0.5.0.5; (2): 0.27,0.73;

I

Belie/Nenvork Anaiysis of Direcr Cos! Risk in Btdding i'onswtic!ion 200

probability(GroundConditions 1 ArchlgclSrvy, Geology) 1 i

(0.0): 0.17,0.83; (O, 1): 0.5,O.s'; (1. O): 0.4,0.6: (1. 1): 0-77.0.23:

1

probability(LndRltdNulDsstr [ Geology) {

(O): O. 17.0.83; (1): 0.3,0.7:

1

probabili&(BudgetRevisions 1 Owner)

(O): 0.37.0.63; (1): O. 17.0.83;

1

probabiIity(FundingSource 1 Govemrnent. GvmrnnrSpndngOnCnstrctn) {

(O, O): 0.37.0.55.0.08: (O, 1): 0.33.0.5, O. 17; (1, O): 0.46.034.0.2; (1. 1): 0.47.0.33,O.Z;

I

Belief Nenvork Analysis of Direct Cosf Risk in Building Consrrucrion 20 1

pro babili~(SiteAccess)

partitions I

node ConstnictionDelays 1 I

level O parent EnvironrnentalDelays, level 1 state O. level 1 stare 1, level 2 parent FailureDelays. lever 3 state O, Ievel 3 state 1. level4 parent DesignDelays. IeveI 5 state O. level 6 parent LogisticsDelqs, level 7 state O, level 8 parent LabourDelays. level9 state O. Ievcl 9 smte 1. Ievel 7 state 1. lever 8 parent LabourDelays, level9 state O. level 9 state 1. level 5 state 1, level 6 parent LogisricsDelays. IeveI 7 state O, level 8 parent LabourDelays. leve19 state O. level9 state i, level 7 state 1, level 8 parent LabourDelap. level 9 stare O, level 9 state 1

1

node WrkQnttyDvtns {

level O parent DesignChanges. level 1 state O. Ievel 1 state 1, level 2 parent DefectiveWork, level3 state O, level 3 state 1, level4 parent TnncRqrrnntChng, level 5 state O, level 6 parent GroundConditions. level 7 state O, level 8 parent DesignQuality. level 9 stare O. level 9 state 1. level 7 stare 1, level 8 parent DesignQuality, level 9 state 0. level9 state 1, level 5 state 1. level6 parent GroundConditions. Ievel 7 state 0.

Belief Nenvork rlnalysis of Direcr Cosr Risk in Building Consrrucrion 202

IeveI 8 parent DesignQuality, level 9 state O. level9 state 1, level 7 state 1, level 8 parent DesignQuality, level9 state O. Ievel9 state L. Ievel5 state 2. level 6 parent GroundConditions, level 7 statc O, level 8 parent DesignQuality. level9 state O. leveI9 state 1. level 7 state 1, level8 parent DesignQuality, level9 state O. level 9 state 1

1

node Materials hortase

level O parent MaterialsDeIivery. Ievel 1 state i. Ievel 1 state O. Ievel 2 parent MaterialWaste, level 3 state O, levcl4 parent MtrlEqpmntLss. level 5 state O. level 6 parent DesignChanges. level 7 state O, lcvel 7 state 1, levd 5 state 1, IeveI 6 parent DesignChanges. level 7 state O? level 7 state 1, level3 state 1, level 4 parent MtrlEqprnntLss, level 5 state O, level 6 parent DesignChanges. level 7 state O. Ievel 7 state 1, level 5 state 1. level 6 parent DesignChanges. level 7 state O. level 7 state 1

1

level O parent PhysclPrjctS~ Ievel 1 state 1, level2 parent Crnpui-ficwtyOnSt. level 3 state O. level 3 state 1. level4 parent NrnbrOfWrkrsOnSt, level 5 state O, level 5 state 1, level 6 parent SiteAccess. tevel 7 state O. Ievel 7 state 1, Ievel 1 state O. level 2 parent CmptngActvtyOnSt level3 state O, IeveI4 parent NrnbrOtWrkrsOnS~ level 5 state 0, level 6 parent SiteAccess. level 7 state 0, level 7 state 1. level 5 state 1, level 6 parent SiteAccess,

Belief Nenvork Anuiysis of Direct Cost Risk in Buildrng Consrnicrion 203

Ievel7 state O, Ievel 7 state 1, Ievel3 state 1. Ievel4 parent NmbrOfWrkrsOnSt. Ievel 5 state O, level 6 parent SiteAccess, level 7 state O. level 7 state 1, level 5 state 1. level6 parent SiteAccess, level 7 strite 0. level 7 state !

1

node StblEqprnntAvlblty i

level O parent LclCnstrctnMrkt. level 1 state O, level 1 srate 1. level2 parent Geography, level3 state 2, level3 state 1. level3 parent MulEqpmntLss. level5 state O, level 5 state 1. IeveI 3 state O, leveI 4 parent MtriEqpmntLss. level 5 state O, Ievel 5 state 1. Ievel 1 state 2, level 2 parent Grography, Ievel 3 state 2, level 3 state 1, level3 parent MtrlEqprnntLss, level 5 state O, level 5 state 1, level 3 state O, level 4 parent MtrlEqprnntLss, level 5 state O, level 5 state 1

Belief h'envork Analysis oJ Direct Cosr Risk in Building Comfrtrction 204

Appendix M: Mode1 Validation Results

Belief Nehvork .Inaiysis of Direct Cost Rrsk in Bur!drng Constnrcrion 205

Validation test #1 results

Contract Arnount: $5.1 95 250 Final Contract Value: $0,417,707 Fixed Cost Amaunt: $3,736,760 Final Contract Increase: 62.00% Unit Pnce Amount: 81.458.490

Details: Originally Planned Scope of Work radically Altered Additional Scope through Extensive Change orders Schedule Delays Costs arising from extended contrad duration: Costs arising from acceleration of work Budget revisions aIIowed lnadequate site investigation Poor estimating Deliberate change o f requirements lncreased volume of work cornpleted Overtime major - extended hours and weekends Loss o f productivity Labour congestion

Belief ~Venvork Anaiysis of Direct Cosf Risk in Building Consrnrcrion 206

Validation test #2 results

Contract Pmount: $1,930,055 Final Contract Value: $3,442,484 Final Contract Increase: 78.40%

Details: Excessive overtime lncreased manhour c o s tower productivity excessive modifications inromplete design, errors in design construction delays poor site accesdegress suitable equipment unavailability no budget revisions lncreased volume of work completed

1 Exoected Values

Belief Nenvork Analysts of Direct Cosf Risk in Building Constnrcrion 207

Documents

NOTE TO USERS - University of Toronto T-Space · range of cost overnins for each of the Equipment, Labour and Material Costs on a construction project. Two completed p-ojects were